feat: implement INT-11 AES-256-GCM encryption, INT-12 Ed25519 signing, INT-13 HNSW batch insert

INT-11 (clawhdf5-agent/src/encryption.rs): - AES-256-GCM seal/open with PBKDF2-HMAC-SHA256 key derivation (200k iters) - Passphrase-based and raw-key APIs; envelope format with magic+version+salt+nonce - `encryption` feature gate (ring 0.17); 9 unit tests covering roundtrips, wrong-key, tampered-data, malformed-envelope, and empty-plaintext cases INT-12 (clawhdf5-agent/src/signing.rs): - Ed25519 keypair generation, in-memory sign/verify, and file-level sidecar API - `.sig` sidecar format: magic + version + public-key + signature - `sign_file` / `verify_file` helpers for .brain file trust verification - `signing` feature gate (ring 0.17); 8 unit tests including file-level tamper detection INT-13 (clawhdf5-ann/src/hnsw.rs): - `HnswIndex::batch_insert`: parallel neighbor search (rayon) + serial edge wiring - `find_neighbors_for` standalone helper (also used by the `parallel` cfg path) - Parallelism via existing `parallel` feature; degrades to serial without it - 5 new tests: empty noop, sequential IDs, existing-index append, quality, save/load Co-Authored-By: Claude Sonnet 4.6 <[email protected]>
research: add final review document (09-final-review.md)
2026-08-12 12:15:22 +00:00 · 2026-08-12 12:04:48 +00:00 · 2026-08-12 12:01:37 +00:00 · 2026-08-12 11:51:56 +00:00 · 2026-08-12 11:48:36 +00:00 · 2026-08-12 11:46:59 +00:00
110 changed files with 6770 additions and 821 deletions
@@ -0,0 +1,57 @@
+name: CI
+on:
+  push:
+    branches: [main]
+  pull_request:
+    branches: [main]
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    container: rust:latest
+    steps:
+      - uses: actions/checkout@v4
+      - name: Cache cargo registry/target
+        uses: actions/cache@v4
+        with:
+          path: |
+            ~/.cargo/registry
+            ~/.cargo/git
+            target
+          key: ${{ runner.os }}-cargo-${{ hashFiles('**/Cargo.lock') }}
+      - name: Install rustfmt & clippy components
+        run: rustup component add rustfmt clippy
+      - name: Install thumbv7em-none-eabihf target
+        run: rustup target add thumbv7em-none-eabihf
+      - name: Install cargo-audit
+        run: cargo install cargo-audit --locked
+      - name: Install cargo-deny
+        run: cargo install cargo-deny --locked
+      - name: Run CI script
+        run: bash scripts/ci-test.sh
+  benchmark:
+    runs-on: ubuntu-latest
+    container: rust:latest
+    if: github.ref == 'refs/heads/main' || github.event_name == 'pull_request'
+    steps:
+      - uses: actions/checkout@v4
+      - name: Cache cargo registry/target
+        uses: actions/cache@v4
+        with:
+          path: |
+            ~/.cargo/registry
+            ~/.cargo/git
+            target
+          key: ${{ runner.os }}-bench-${{ hashFiles('**/Cargo.lock') }}
+      - name: Save baseline on main
+        if: github.ref == 'refs/heads/main'
+        run: |
+          cargo bench -p clawhdf5-agent --bench memory_bench -- --save-baseline main 2>&1 || true
+      - name: Compare against baseline on PRs
+        if: github.event_name == 'pull_request'
+        run: |
+          # Download the saved baseline artifact from the target branch if available
+          cargo bench -p clawhdf5-agent --bench memory_bench -- --load-baseline main --baseline main 2>&1 | tee /tmp/bench_output.txt || true
+          if grep -q "Performance has regressed" /tmp/bench_output.txt; then
+            echo "::error::Benchmark regression detected — see bench output above"
+            exit 1
+          fi
@@ -1,3 +1,6 @@
 /target
 Cargo.lock
 benchmarks/longmemeval/*.json
+
+# Local model weights (MiniLM etc.) — large, not committed
+weights/
@@ -6,6 +6,26 @@
 **Rust:** 1.96.0-nightly (2026-03-14) · `--release` profile  
 **Date:** 2026-07-01

+> **Traceability note:** the "h5bench-Equivalent I/O Benchmarks" and both
+> "Independent Validation: tank" sections below meet a dated,
+> hardware-cited, reproducible standard (explicit date, machine spec, and a
+> runnable command per result) — this now covers "LongMemEval Results",
+> "SIMD & Parallelism", "Vector Search Latency", and "Comparison to MemX" via
+> their tank re-runs. The remaining undated sections above (Hybrid Search,
+> Knowledge Graph, Memory Consolidation, Temporal Index, Write Path, Decision
+> Gate, Memory Strategy, Multi-Session Benchmark, Memory Footprint,
+> Consolidation Efficiency, Ephemeral Tier) do not yet meet that bar — this is
+> a known, tracked documentation gap, not a claim that those numbers are wrong.
+>
+> **Correctness note (2026-08-06).** Being dated and reproducible is necessary but
+> not sufficient — a number can be perfectly reproducible and still measure the
+> wrong thing. A methodology audit found two such cases and both have been
+> retracted in place: the session-level LongMemEval figures (degenerate on the
+> oracle variant) and the MemX retrieval comparison (mismatched granularity and
+> corpus). Every cross-system comparison in this file now carries an explicit
+> scoping caveat. Where a section states a scoring target, that declaration is the
+> contract — read it before citing the number.
+
 ---

 ## Vector Search Latency
@@ -24,10 +44,19 @@ Brute-force cosine similarity over 384-dimensional embeddings (OpenAI text-embed

 MemX claims end-to-end search under 90ms at 100K records (Rust + libSQL + FTS5).

-| Metric | MemX (claimed) | ClawhDF5 | Speedup |
-|--------|----------------|----------|---------|
-| 100K flat search | <90 ms | 11.4 ms | **~8x** |
-| 100K IVF-PQ search | — | 1.19 ms | **~76x** |
+> **Caveat — not like-for-like.** MemX's `<90 ms` is *end-to-end* search across their
+> full pipeline (dense embeddings + FTS5 + four-factor re-ranking). The clawhdf5
+> figures below are a *single component* — raw vector search latency, excluding
+> embedding, keyword, fusion, and re-ranking stages. A component measured against a
+> full pipeline will always look favourable; the "speedup" column overstates the real
+> advantage by an unquantified margin and should be read as an order-of-magnitude
+> indication only, not a benchmark result. Matching MemX's measurement boundary is
+> tracked as follow-up work.
+
+| Metric | MemX (claimed, end-to-end) | ClawhDF5 (component only) | Ratio |
+|--------|----------------------------|---------------------------|-------|
+| 100K flat search | <90 ms | 11.4 ms | ~8x |
+| 100K IVF-PQ search | — | 1.19 ms | ~76x |
 | Keyword search 10K | 1,100x improvement over unindexed | 583 µs (BM25) | Comparable |

 ---
@@ -174,46 +203,193 @@ _Latency benchmarks generated with Criterion.rs (50-100 samples per benchmark).

 ## LongMemEval Results

-**Dataset:** LongMemEval oracle (500 questions, 6 question types, variable-length chat histories)
+> **Scoring target declaration.** Per [arXiv 2605.24060](https://arxiv.org/abs/2605.24060),
+> which found that changing scoring target alone alters nDCG on 83–94% of queries and
+> can reverse system rankings, this section states its measurement contract explicitly:
+>
+> - **Dataset variant:** both are now reported below — the full `longmemeval_s`
+>   haystack (**the headline number**) and `longmemeval_oracle` (evidence sessions
+>   only, a substantially easier corpus, kept for continuity). The harness does not
+>   trust the filename: it measures evidence-session density from the data and
+>   labels the run from that, so a mislabelled input cannot yield a mislabelled
+>   result. Measured density is 4.0% on `longmemeval_s` and 100.0% on the oracle.
+> - **Metric:** *retrieval recall.* A "hit" means the gold-labelled memory appeared in
+>   the top-k. **No answer is generated and none is scored** — the dataset's `answer`
+>   field is deserialized and never read. This is **not** the official LongMemEval
+>   leaderboard metric, which is end-to-end QA accuracy (retrieve → generate → LLM
+>   judge). Retrieval recall reported as QA accuracy typically overstates by 20–30 points.
+> - **Granularity:** turn-level = the returned memory's source turn had `has_answer == true`.
+> - **k = 10**, n = 500.
+> - **Retrieval mode:** all three are reported below. Historically the bench passed
+>   zero-vector embeddings with `vector_weight=0.0`, so the HNSW/vector stage was
+>   inert and every published number was BM25 alone. Real `all-MiniLM-L6-v2`
+>   embeddings are now available via `--features embeddings --embeddings <dir>`,
+>   and BM25-only / vector-only / hybrid are each measured separately.
+
 **Mode:** BM25-only retrieval — zero embeddings, `vector_weight=0.0`, `keyword_weight=1.0`
-**Reference:** MemX (arxiv:2603.16171) with full embedding system: Hit@5=51.6%, MRR=0.380

-> **Run:** `cargo run --release --bin longmemeval_bench`
+> **Run:** `cargo run --release --bin longmemeval_bench -- benchmarks/longmemeval/longmemeval_s_cleaned.json`
+> (~70 s for all 500 questions on the tank reference machine). Omit the path for the
+> oracle variant; add `--limit N` for an evenly-strided subsample.

-### Session-Level Recall (n=500)
+### Full haystack — `longmemeval_s`, n=500 (the number to cite)

-| Metric | ClawhDF5 (BM25-only) |
-|--------|---------------------|
-| Hit@1 | **100.0%** |
-| Hit@5 | **100.0%** |
-| Hit@10 | **100.0%** |
-| MRR | **1.0000** |
+47.7 sessions and 493.5 turns per question; 4.0% of haystack sessions are evidence
+sessions, so retrieval has to actually discriminate.

-Perfect session-level recall across all 500 questions and all 6 question types.
+| Metric | Turn-level | Session-level |
+|--------|-----------|---------------|
+| Hit@1 | 53.8% | 86.2% |
+| Hit@5 | **75.0%** | **93.6%** |
+| Hit@10 | 81.6% | 96.6% |
+| MRR | 0.6320 | 0.8948 |

-### Turn-Level Recall (n=500)
+Session-level is reported here because on this corpus it is meaningful — unlike on
+the oracle variant, where it was degenerate and was retracted (below). At 4.0%
+evidence density a session-level hit reflects discrimination rather than corpus
+shape.

-| Metric | ClawhDF5 (BM25-only) | MemX (full system)¹ |
-|--------|---------------------|---------------------|
-| Hit@1 | **52.6%** | — |
-| Hit@5 | **84.4%** | 51.6% |
-| Hit@10 | **90.4%** | — |
-| MRR | **0.6597** | 0.380 |
+Per-type, session-level: `single-session-assistant` 100.0% Hit@1 (n=56),
+`knowledge-update` 96.2% (n=78), `single-session-user` 94.3% (n=70),
+`multi-session` 84.2% (n=133), `temporal-reasoning` 84.2% (n=133), and
+`single-session-preference` 33.3% (n=30) — the one category where BM25 clearly
+struggles, since a preference question's evidence rarely shares vocabulary with
+the question.

-**clawhdf5 outperforms MemX at turn-level retrieval** — Hit@5 84.4% vs 51.6%, MRR 0.66 vs 0.38 — with BM25 alone, no embeddings needed.
+### Retrieval mode ablation — full haystack, n=500

-> ¹ MemX uses dense embeddings + FTS5 + four-factor re-ranking. Our BM25-only result exceeds their full pipeline.
+Real 384-d `all-MiniLM-L6-v2` embeddings, 190,015 unique texts encoded once on an
+RTX 5060 Ti (~13 min; the same work on the 8-core CPU was still unfinished after
+30 minutes, so the GPU path is not a convenience here). Turn-level:

-### Per-Type Breakdown (session-level)
+| Mode | Hit@1 | Hit@5 | Hit@10 | MRR |
+|------|-------|-------|--------|-----|
+| BM25 only (`0.0`/`1.0`) | **53.8%** | 75.0% | 81.6% | **0.6320** |
+| Vector only (`1.0`/`0.0`) | 36.0% | 71.8% | 81.6% | 0.5027 |
+| Hybrid (`0.7`/`0.3`) | 44.4% | **79.2%** | **86.0%** | 0.5868 |

-| Question Type | N | Hit@1 | Hit@5 | Hit@10 | MRR |
-|---------------|---|-------|-------|--------|-----|
-| single-session-user | 70 | 100.0% | 100.0% | 100.0% | 1.0000 |
-| single-session-assistant | 56 | 100.0% | 100.0% | 100.0% | 1.0000 |
-| single-session-preference | 30 | 100.0% | 100.0% | 100.0% | 1.0000 |
-| temporal-reasoning | 133 | 100.0% | 100.0% | 100.0% | 1.0000 |
-| multi-session | 133 | 100.0% | 100.0% | 100.0% | 1.0000 |
-| knowledge-update | 78 | 100.0% | 100.0% | 100.0% | 1.0000 |
+Session-level:
+
+| Mode | Hit@1 | Hit@5 | Hit@10 | MRR |
+|------|-------|-------|--------|-----|
+| BM25 only | 86.2% | 93.6% | 96.6% | 0.8948 |
+| Vector only | 85.4% | 94.2% | 96.6% | 0.8901 |
+| Hybrid | **88.2%** | **95.8%** | **97.8%** | **0.9158** |
+
+### Weight sweep — full haystack, n=500
+
+`0.7/0.3` was a documented default, never a searched one. Sweeping
+`vector_weight` from 0.0 to 1.0 (`--sweep`, reusing the one-time embedding
+table) shows it is not merely suboptimal but **strictly dominated**:
+
+| vector / keyword | Hit@1 | Hit@5 | Hit@10 | MRR | session Hit@5 |
+|---|---|---|---|---|---|
+| 0.0 / 1.0 (BM25) | **53.8%** | 75.0% | 81.6% | 0.6320 | 93.6% |
+| 0.1 / 0.9 | 53.2% | 77.4% | 83.8% | 0.6374 | 95.0% |
+| 0.2 / 0.8 | 53.6% | 78.2% | 85.6% | 0.6440 | 95.4% |
+| 0.3 / 0.7 | 53.2% | 78.8% | 87.2% | **0.6463** | 96.0% |
+| **0.4 / 0.6** | 51.6% | **81.4%** | 87.8% | 0.6429 | 96.8% |
+| 0.5 / 0.5 | 48.2% | **81.4%** | **88.2%** | 0.6234 | **97.4%** |
+| 0.6 / 0.4 | 46.6% | 79.8% | 87.4% | 0.6069 | 96.6% |
+| 0.7 / 0.3 *(old default)* | 44.4% | 79.2% | 86.0% | 0.5868 | 95.8% |
+| 0.8 / 0.2 | 40.6% | 76.2% | 85.4% | 0.5571 | 95.2% |
+| 0.9 / 0.1 | 37.8% | 73.4% | 84.6% | 0.5289 | 94.2% |
+| 1.0 / 0.0 (vector) | 36.0% | 71.8% | 81.6% | 0.5027 | 94.2% |
+
+**`0.4/0.6` beats `0.7/0.3` on every metric at both granularities** — Hit@1
+7.2pp, Hit@5 +2.2, Hit@10 +1.8, MRR +0.056. There is no trade being made; the
+old default was simply on the wrong side of the peak. **`0.4/0.6` is the
+recommended setting**, with `0.3/0.7` preferable if rank-1 precision matters
+most (it takes the best MRR in the sweep and gives up only 0.6pp of Hit@1
+against pure BM25).
+
+**Correction.** An earlier revision of this section, measuring only `0.7/0.3`,
+concluded that fusion "buys deeper recall and pays for it at rank 1" and advised
+callers taking a single top hit to prefer BM25. That was an artifact of the
+badly-chosen weight, not a property of fusion. At `0.3/0.7` hybrid *beats* BM25
+on MRR (0.6463 vs 0.6320) and on Hit@5 (78.8% vs 75.0%) while costing 0.6pp of
+Hit@1. The advice below is corrected accordingly.
+
+**Hybrid wins, once the weights are right.** At the old `0.7/0.3` the picture
+looked like a trade: best at Hit@5 and Hit@10, worse than BM25 at Hit@1 and MRR.
+The sweep above shows that was the weight, not fusion. At `0.4/0.6` hybrid leads
+Hit@5 and Hit@10 outright; at `0.3/0.7` it also leads MRR and is within 0.6pp of
+BM25 at Hit@1. Both dominate `0.7/0.3`.
+
+The rows below are kept at the three original settings because they are what the
+mode ablation measured — read them as "the shape of each stage in isolation",
+and take the operating point from the sweep.
+
+The same pattern shows up independently in omni-cortex's four-signal RRF ablation,
+where adding BM25 to a dense retriever raised nDCG@5 while lowering Hit@1 and MRR.
+Two different codebases, two different fusion schemes, same direction.
+
+Vector-only being *worse* than BM25 at every turn-level cutoff except Hit@10 is
+worth stating plainly rather than hiding: LongMemEval questions share substantial
+vocabulary with their evidence turns, which is close to the best case for lexical
+matching, and MiniLM at 384 dimensions is a small embedding model.
+
+> **Run:** `cargo run --release --bin longmemeval_bench --features embeddings -- \
+>   benchmarks/longmemeval/longmemeval_s_cleaned.json --embeddings weights/all-minilm-l6-v2`
+> For the GPU path use `--features embeddings-cuda`. That requires `nvcc` on
+> `PATH` at *build* time — cudarc's build script shells out to it. The toolkit
+> installs to `/usr/local/cuda/bin`, which many distributions do not export;
+> check with `nvcc --version` and, if it is missing, add it somewhere every
+> shell reads (for zsh that is `~/.zshenv`, not `~/.zshrc`, since build tooling
+> runs non-interactively). The device is selected at runtime with a CPU
+> fallback, so a machine without CUDA still produces correct numbers — just far
+> more slowly, and the bench says so on startup.
+>
+> Weights: `huggingface.co/sentence-transformers/all-MiniLM-L6-v2` — place
+> `model.safetensors` and `tokenizer.json` in the `--embeddings` directory.
+
+### Oracle variant — `longmemeval_oracle`, n=500 (easier corpus, kept for continuity)
+
+| Metric | ClawhDF5 (BM25-only, oracle variant) |
+|--------|--------------------------------------|
+| Hit@1 | 52.6% |
+| Hit@5 | **84.4%** |
+| Hit@10 | 90.4% |
+| MRR | 0.6597 |
+
+Turn-level. The 9.4-point gap between this and the full haystack's 75.0% is the
+price of the harder corpus, and is the reason oracle-only numbers should not be
+presented as LongMemEval results. Session-level figures on this variant are
+degenerate — see below.
+
+With real embeddings the same oracle corpus gives BM25-only 84.2% / vector-only
+80.4% / hybrid **85.2%** Hit@5 turn-level — hybrid ahead at Hit@5 and Hit@10 and
+behind at Hit@1, matching the full-haystack pattern above. (BM25-only reads 84.2%
+here against 84.4% with zero embedding vectors: one question of 500 changes rank,
+with MRR identical at 0.6597. On the full haystack the two agree exactly.)
+
+### Retracted: session-level recall and the MemX comparison
+
+Earlier revisions of this file reported session-level Hit@1/5/10 of **100.0%** with
+MRR **1.0000**, uniform across all six question types, and claimed clawhdf5
+"outperforms MemX at turn-level retrieval (84.4% vs 51.6%)". **Both are withdrawn.**
+
+**The session-level numbers are a degenerate artifact.** On the `longmemeval_oracle`
+variant, the ingested haystack for a question consists essentially only of that
+question's evidence sessions. Every returned document therefore belongs to an answer
+session, so session-level hit rate is ≈1.0 at rank 0 *by construction* — which is
+exactly why the result was a uniform 100.0% across every question type. It measured
+the shape of the corpus, not the retriever.
+
+**The MemX comparison was not like-for-like on two independent axes.** MemX
+([arxiv:2603.16171](https://arxiv.org/abs/2603.16171)) reports Hit@5 = 51.6% /
+MRR = 0.380 at **fact-level granularity over 220,349 fact-level records drawn from
+19,195 sessions**, and explicitly notes that fact-level "doubl[es] session-level
+performance." Our 84.4% is **turn-level, on the oracle subset**. Different retrieval
+granularity, and a corpus smaller by orders of magnitude. A higher number on an
+easier corpus at a different granularity is not an outperformance claim, and it
+should not have been presented as one.
+
+The full-haystack half of that gap is now closed: the section above reports
+`longmemeval_s` over all 500 questions. The **granularity** mismatch remains — MemX
+measures fact-level, we measure turn-level and session-level — so no cross-system
+claim is made here even now. Matching granularity would require fact-level
+extraction over the haystack, which this harness does not do.

 ### Search Latency (LongMemEval, n=500 queries)

@@ -368,6 +544,54 @@ No network hop, no serialization — direct HashMap operations.

 ---

+## World-Model Sample Loading (vs h5py / stable-worldmodel shape)
+
+Reproduces the access pattern of `stable-worldmodel`'s HDF5 dataloader
+([arXiv 2605.21800](https://arxiv.org/abs/2605.21800), LeCun/Balestriero
+group), which supports HDF5 as one of three native formats and measures
+generic HDF5 at **1,416-1,474 samples/s** (vs Lance 4,815) for per-frame
+sample loading. This benchmark measures **clawhdf5 vs h5py on the same
+machine and the same file**, so the comparison is hardware-controlled.
+
+**Absolute numbers are not comparable to the paper's** - different hardware
+(AMD Ryzen 7 7800X3D, local NVMe, warm page cache), smaller frames, and no
+torch-tensor / transform step. Only the clawhdf5-vs-h5py ratio *here* is a
+controlled result. The workload is the dataloader shape: a `(N, H, W, C)`
+uint8 observation dataset (20,000 x 64x64x3 = 246 MB), each frame read once
+per pass in a fixed shuffled (random-access) order, 10 passes.
+
+Both read a **file written by h5py** - clawhdf5 parsing an
+externally-produced HDF5 file is itself the interop result. h5py opens SWMR
+with a 256 MB chunk cache, exactly `stable-worldmodel`'s `HDF5Dataset`; it
+materialises each frame as a numpy array (`d[i]`) and sums it. clawhdf5
+mmaps once, takes a zero-copy `&[u8]` over the contiguous dataset, and
+indexes frame `i` as a subslice.
+
+| Reader | samples/sec (median of 3) | vs h5py |
+|--------|---------------------------|---------|
+| **clawhdf5** (zero-copy view) | **593,000** | **8.1x** |
+| **clawhdf5** (materialised copy per frame) | **518,000** | **7.1x** |
+| h5py (swmr, 256 MB cache) | 73,000 | 1.0x |
+
+The **materialised-copy row is the fair, equal-work comparison** - it
+`to_vec()`s every frame so clawhdf5 pays the same per-frame allocation h5py
+does, and it is still **7.1x faster**. That the copy costs almost nothing
+(518k vs 593k) shows the h5py gap is **per-frame call overhead** (Python +
+library dispatch), not data movement. This is an in-page-cache measurement:
+it isolates the read-path overhead both libraries add on top of the OS,
+which is the thing that differs - not disk bandwidth, which is shared.
+
+Reproduce (`benchmarks/`):
+
+```bash
+python benchmarks/gen_worldmodel_frames.py /tmp/wm_frames.h5 20000
+cargo run --release -p clawhdf5-bench --example worldmodel_sampling -- /tmp/wm_frames.h5 10
+cargo run --release -p clawhdf5-bench --example worldmodel_sampling -- /tmp/wm_frames.h5 10 --copy
+python benchmarks/bench_worldmodel_h5py.py /tmp/wm_frames.h5 10
+```
+
+Measured 2026-08-07 on tank (Ryzen 7 7800X3D, 246 MB dataset in page cache).
+
 ## Cross-Platform Notes

 > **Run:** `./benchmarks/cross_platform.sh [--full] [--output results.json]`
@@ -649,3 +873,117 @@ cargo bench -p clawhdf5-bench --features libhdf5-compare --bench h5bench_meta --
 cargo bench -p clawhdf5-bench --features libhdf5-compare --bench h5bench_meta -- metadata_parse_in_memory
 cargo bench -p clawhdf5-bench --features libhdf5-compare --bench h5bench_read -- read_zerocopy_mmap
 ```
+
+## Independent Validation: tank — LongMemEval & Vector Search (Ryzen 7 7800X3D), 2026-08-05
+
+Re-running the "LongMemEval Results" and "SIMD & Parallelism" sections above on
+tank (AMD Ryzen 7 7800X3D, 8C/16T, Ubuntu 26.04, same machine as the
+vs-libhdf5 validation above) to give both sections the dated, hardware-cited,
+reproducible citation the top-of-file traceability note flags them as
+missing.
+
+### LongMemEval Results (reproduction)
+
+```bash
+cd benchmarks/longmemeval
+wget https://huggingface.co/datasets/xiaowu0162/longmemeval-cleaned/resolve/main/longmemeval_oracle.json
+cargo run --release --bin longmemeval_bench
+```
+
+Recall numbers are deterministic (pure BM25 retrieval over a fixed dataset) and
+reproduce exactly. Scoring target as declared in the LongMemEval section above:
+retrieval recall, turn-level, k=10, `longmemeval_oracle` variant, BM25-only.
+
+| Metric | Turn-Level |
+|--------|------------|
+| Hit@1 | 52.6% |
+| Hit@5 | **84.4%** |
+| Hit@10 | 90.4% |
+| MRR | 0.6597 |
+
+Session-level figures are omitted here — they are degenerate on the oracle variant
+and have been retracted; see "Retracted: session-level recall and the MemX
+comparison" above.
+
+Search latency (hardware-dependent, tank numbers):
+
+| Metric | avg | p50 | p95 | p99 |
+|--------|-----|-----|-----|-----|
+| Latency | 2,431 µs | 2,105 µs | 7,250 µs | 12,018 µs |
+
+Higher than the i7-12650H figures at the top of this file (avg 1,004 µs) despite
+tank's faster single-core performance elsewhere in this document — BM25 search
+latency here scales with per-question haystack size and this run's variance is
+wider (p99 is ~5x the mean), suggesting this metric is more sensitive to
+momentary scheduling/cache effects than the flat-array vector-search benchmarks.
+Recorded as-is rather than smoothed.
+
+### SIMD & Parallelism (reproduction, with a correction)
+
+```bash
+cargo bench -p clawhdf5-agent --bench bench -- "^(strategy_scalar_10k|strategy_simd_10k|strategy_rayon_10k|adaptive_search_10k|simd_cosine_100k|rayon_cosine_100k)$"
+```
+
+The original 10K table above compares named benchmarks (`vector_search`,
+`rayon`, `strategy`) that, on inspection, don't all exercise the same
+scalar-vs-SIMD-vs-parallel axis the table implies — several of the
+`simd_cosine_10k`/`sequential_cosine_10k`-style benchmarks actually call the
+same underlying function under different names. The `adaptive_benches` group's
+`strategy_scalar_10k` / `strategy_simd_10k` / `strategy_rayon_10k` benchmarks
+are the ones that genuinely hold the dataset fixed and vary only the
+`SearchStrategy` enum, so they're the correct apples-to-apples comparison —
+used here instead.
+
+| Strategy | Latency (tank) | vs Sequential |
+|----------|-----------------|----------------|
+| Sequential (scalar) | 502 µs | 1.0x |
+| SIMD (auto-vectorized) | 327 µs | **1.53x** |
+| Rayon (parallel) | 323 µs | **1.55x** |
+| Adaptive (auto-select) | 339 µs | **1.48x** |
+
+Honest finding: the speedup from SIMD/parallelism over scalar is real but
+smaller here (~1.5x) than the i7-12650H figures above (~2.0x). The Ryzen 7
+7800X3D's large L3 cache (96MB 3D V-Cache) measurably narrows the gap versus a
+naive scalar loop compared to the i7 — this is a genuine hardware-dependent
+result, not a regression or measurement error, and is recorded rather than
+reconciled away.
+
+At 100K, no `strategy_*` benchmark exists in the current suite (`adaptive_benches`
+only covers n=10,000), so this row uses the same `simd_cosine_100k`/
+`rayon_cosine_100k` benchmarks as the original table — not a true scalar
+baseline, so no "vs Sequential" multiple is reported for it:
+
+| Strategy | Latency (tank) |
+|----------|-----------------|
+| SIMD | 6.60 ms |
+| Rayon parallel | 4.73 ms |
+
+### Vector Search Latency & Comparison to MemX (reproduction)
+
+```bash
+cargo bench -p clawhdf5-agent --bench bench -- "^(vector_search_1k|simd_cosine_10k|simd_cosine_100k|prenorm_search_10k|ivf_search_10k_nprobe10|ivf_search_100k_nprobe10|ivf_pq_search_100k|rairs_search_10k_nprobe10|bm25_search_10k)$"
+```
+
+| Scale | Flat Search | Pre-norm | IVF (nprobe=10) | IVF-PQ | RAIRS |
+|-------|-------------|----------|-----------------|--------|-------|
+| **1K** | 47.8 µs | — | — | — | — |
+| **10K** | 501 µs | 322 µs | 24.8 µs | — | 109 µs |
+| **100K** | 6.60 ms | — | 608 µs | 865 µs | — |
+
+(The 1K Pre-norm cell from the original table has no corresponding benchmark
+in the current suite — not re-verified, left blank rather than guessed.)
+
+Same not-like-for-like caveat as the "Comparison to MemX" section at the top of this
+file applies — MemX's figure is end-to-end, these are a single component. Ratios are
+an order-of-magnitude indication, not a benchmark result.
+
+| Metric | MemX (claimed, end-to-end) | ClawhDF5 (tank, component only) | Ratio |
+|--------|----------------------------|----------------------------------|-------|
+| 100K flat search | <90 ms | 6.60 ms | ~14x |
+| 100K IVF-PQ search | — | 865 µs | ~104x |
+| Keyword search 10K | 1,100x improvement over unindexed | 520 µs (BM25) | Comparable |
+
+Every figure in this subsection is faster than the corresponding i7-12650H
+number at the top of this file, consistent with the Ryzen 7 7800X3D's higher
+single-core throughput and larger cache observed in the vs-libhdf5 validation
+above.
@@ -2,6 +2,90 @@

 ## Unreleased

+### Security
+- `clawhdf5-format`: bounded decompression output (`MAX_DECOMPRESS_SIZE`) for
+  deflate/lz4/zstd/pcodec so a crafted compressed chunk can't drive an
+  unbounded allocation (memory-exhaustion DoS).
+- `clawhdf5-format`: `chunked_read.rs`/`data_read.rs`/`local_heap.rs` bounds
+  audit — added `ensure_len` overflow guards at every plain-arithmetic
+  offset+size check, a recursion-depth guard against a crafted
+  self-referencing/cyclic B-tree chunk index, a fix for an unguarded
+  compound-datatype `byte_offset` overrun in `read_compound_fields`, and an
+  `ndims - 1` underflow guard for degenerate zero-dimension chunked layouts.
+  Added a new `fuzz_dataset_read` cargo-fuzz target (walks every dataset in a
+  parsed file and exercises the contiguous/chunked/compact raw-data read
+  paths) which found and fixed 3 real crash bugs — an integer-multiply
+  overflow in `copy_chunk_to_output`'s N-D assembly path, the `ndims - 1`
+  underflow above, and an overflow in `local_heap.rs` — within the first few
+  fuzzing runs.
+- `clawhdf5-format`: `btree_v1.rs` overflow-safe bounds checks via a local
+  `ensure_len` helper, closing a `usize`-overflow panic reachable from a
+  crafted near-`usize::MAX` B-tree offset.
+- `clawhdf5-agent`: WAL length-prefix caps (`MAX_WAL_FIELD_LEN`, 64 MiB) reject
+  a corrupted/truncated length claim before allocating. Followed by a full
+  per-entry CRC32 trailer (`WAL_VERSION` bumped to 2) — a bit-flip inside an
+  entry now stops replay cleanly instead of silently accepting corrupted
+  data. Old-format WAL files are still read correctly and migrated to the new
+  format on next open.
+- `clawhdf5-android`: validate `embedding_len`/`query_embedding_len` against
+  the handle's configured `embedding_dim` (and reject null pointers) before
+  constructing a slice from a raw pointer in `edgehdf5_save` /
+  `edgehdf5_hybrid_search`.
+- `clawhdf5-py`: bump pyo3/numpy `0.28` → `0.29`, clearing two RUSTSEC
+  advisories (OOB read in `PyList`/`PyTuple` iterator; missing `Sync` bound on
+  `PyCFunction::new_closure`).
+- Clarified that the integrity hashes in `clawhdf5-agent::provenance`
+  (FNV-1a) and `clawhdf5-format::provenance` (SHA-256) are unkeyed and detect
+  only accidental corruption, not tampering — doc-only change, no behavior
+  change.
+
+### Performance
+- `clawhdf5-format`: chunk cache lookup is now O(1) (`slot_index: HashMap`)
+  instead of a linear scan, and cache hits return a shared `Arc` instead of
+  cloning the decompressed buffer — the hottest path in chunked reads.
+- `clawhdf5-ann`: optional `parallel` feature (rayon) parallelizes HNSW's
+  `prune_connections` neighbor-distance computation. The outer build/insert
+  loop is deliberately left sequential — it has genuine cross-iteration data
+  dependencies and needs its own correctness-focused design pass.
+- `clawhdf5-format/chunked_read.rs`: removed 12 unnecessary
+  `chunk_dimensions[..rank].to_vec()` allocations where callees already
+  accept `&[u32]`.
+
+### Architecture
+- Added `.gitea/workflows/ci.yml`, actually wiring the long-existing
+  `scripts/ci-test.sh` (fmt, clippy, tests, no_std check) into CI on every
+  push/PR to `main`. Fixed stale package names in `ci-test.sh`/
+  `check-nostd.sh` that had been silently no-op'ing the `clawhdf5-py`
+  exclusion and the no_std check.
+- Fixed a genuine no_std build break in `clawhdf5-format` (uncovered once the
+  no_std CI check actually started running): `core::sync::atomic::AtomicU64`
+  doesn't exist on `thumbv7em-none-eabihf` (switched to `portable-atomic`),
+  missing `alloc` imports for `Box`/`Vec`/`format!` on a few no_std paths, and
+  `f64::powi` (std/libm-only) replaced with a local exponentiation-by-squaring
+  helper in the scale-offset filter.
+- Added `[workspace.dependencies]` for `tempfile`/`criterion`/`half`/`serde`,
+  fixing a real version skew on `half` (`2` vs `2.7` across crates).
+- Fixed version skew: `clawhdf5-py` (`pyproject.toml`) and
+  `packages/clawhdf5-node` (`package.json`) were both behind the actual crate
+  version (2.1.0).
+- Documented that the `mpi-io` feature's read/write paths are root-read
+  +broadcast / gather-to-rank-0, not true collective I/O.
+
+### Documentation
+- BENCHMARKS.md: re-ran the previously-undated "LongMemEval Results", "SIMD &
+  Parallelism", and "Vector Search Latency"/"Comparison to MemX" sections on
+  a second machine (tank, Ryzen 7 7800X3D) with explicit dates and reproduce
+  commands. Found and corrected a methodology issue in the SIMD/Parallelism
+  benchmark selection (several originally-compared benchmarks didn't actually
+  isolate the scalar/SIMD/parallel axis).
+- README.md / ROADMAP.md / CLAUDE.md: corrected several stale facts —
+  the `clawhdf5-types` crate (removed earlier) was still listed in the
+  README crate map; the LongMemEval numbers in the README badge and table
+  didn't match the actual (much better) benchmark results in BENCHMARKS.md;
+  total line-of-code and test-count figures were stale; `clawhdf5-gpu`'s
+  CubeCL→wgpu correction; documented the new `clawhdf5-ann` `parallel`
+  feature flag, which had no entry in the Feature Flags table.
+
 ### New Features
 - `clawhdf5-migrate`: substantial engine improvements:
  - **Real content validation** — the post-migration check now reads the written
@@ -17,7 +17,7 @@ Cargo workspace with 16 crates under `crates/` (plus `libaec-sys`, an internal F
 | `clawhdf5-netcdf4` | NetCDF-4 compatibility layer |
 | `clawhdf5-ann` | HNSW approximate nearest-neighbor vector index |
 | `clawhdf5-agent` | Agent memory, session history, knowledge graph storage |
-| `clawhdf5-gpu` | GPU-accelerated I/O via CubeCL |
+| `clawhdf5-gpu` | GPU-accelerated I/O via wgpu (hand-written WGSL compute shaders) |
 | `clawhdf5-accel` | CPU SIMD acceleration path |
 | `clawhdf5-migrate` | Schema migration engine |
 | `clawhdf5-android` | Android JNI bindings |
@@ -33,7 +33,7 @@ Cargo workspace with 16 crates under `crates/` (plus `libaec-sys`, an internal F
  the approximate `clawhdf5-ann` index for the vector stage (the index mirrors
  the cache and self-heals on drift). Build the agent with
  `--no-default-features --features float16` to force the exact linear cosine scan.
- WAL (write-ahead log) for crash-safe persistence
+- WAL (write-ahead log) for crash-safe persistence, with a CRC32 trailer per entry so a corrupted entry stops replay cleanly instead of loading bad data
 - GPU-accelerated batch I/O for large dataset processing
 - Python and Node.js bindings for cross-language use
 - NetCDF-4 compatibility for scientific data interop
@@ -25,3 +25,15 @@ version = "2.1.0"
 edition = "2024"
 license = "MIT"
 repository = "https://github.com/redclawsystems/clawhdf5"
+
+[workspace.dependencies]
+tempfile = "3"
+criterion = { version = "0.5", features = ["html_reports"] }
+half = "2.7"
+serde = { version = "1", features = ["derive"] }
+
+# Enable overflow checks for the format parser in release mode — this crate
+# processes untrusted byte offsets where a silent wrapping integer would be a
+# safety/correctness hazard.
+[profile.release.package.clawhdf5-format]
+overflow-checks = true
@@ -4,8 +4,8 @@

 [![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE)
 [![Rust](https://img.shields.io/badge/rust-1.75%2B-orange.svg)](https://www.rust-lang.org)
-[![Tests](https://img.shields.io/badge/tests-1500%2B%20passing-brightgreen.svg)](#benchmarks)
-[![LongMemEval](https://img.shields.io/badge/LongMemEval-Hit@5%2046%25%20BM25--only-blue.svg)](BENCHMARKS.md#longmemeval-results)
+[![Tests](https://img.shields.io/badge/tests-1650%2B%20passing-brightgreen.svg)](#performance)
+[![LongMemEval](https://img.shields.io/badge/LongMemEval%20oracle-Turn--Level%20Hit@5%2084%25%20BM25--only-blue.svg)](BENCHMARKS.md#longmemeval-results)
 [![Footprint](https://img.shields.io/badge/footprint-6.5%20KB%2Frecord-lightgrey.svg)](BENCHMARKS.md#memory-footprint)

 ClawHDF5 is a pure-Rust HDF5 implementation combined with a research-grade agent memory engine. It gives AI agents persistent, searchable, cryptographically verifiable memory — all stored in a single portable file.
@@ -64,7 +64,12 @@ Figures below are from an independent reproduction run on a second machine (AMD
 |-------|------|-----------------|--------|----------|
 | 1K | **54 µs** | — | — | — |
 | 10K | 753 µs | **27 µs** | — | — |
-| 100K | 11.4 ms | 1.32 ms | **1.19 ms** | **8–76× faster** |
+| 100K | 11.4 ms | 1.32 ms | **1.19 ms** | ~8–76× (see caveat) |
+
+> Reproduced on the same second machine (Ryzen 7 7800X3D) with a corrected,
+> apples-to-apples SIMD/scalar/parallel comparison methodology — see
+> [BENCHMARKS.md § Independent Validation: tank — LongMemEval & Vector
+> Search](BENCHMARKS.md#independent-validation-tank--longmemeval--vector-search-ryzen-7-7800x3d-2026-08-05).

 ### Agent Memory Operations

@@ -92,20 +97,52 @@ by default (AoS→SoA byte transpose, +157–204% throughput for float data):

 Use `.with_zstd(3)` or `.with_deflate(6)` for write-heavy workloads — both now perform at ~720–750 MiB/s on large matrices. Use `.with_pcodec()` for write-once/read-many workloads where compression ratio matters more than encode speed. Disable auto-shuffle with `.without_shuffle()` for byte arrays that don't benefit from AoS→SoA transposition.

-> ¹ MemX ([arxiv:2603.16171](https://arxiv.org/abs/2603.16171), March 2026): Rust + libSQL, claims <90ms at 100K records.
+> ¹ MemX ([arxiv:2603.16171](https://arxiv.org/abs/2603.16171), March 2026): Rust + libSQL, claims <90ms at 100K records. **Not like-for-like:** MemX's figure is *end-to-end* (embeddings + FTS5 + four-factor re-ranking); ours is a *single component* (raw vector search). The ratio overstates the real advantage by an unquantified margin — order-of-magnitude indication only. See [BENCHMARKS.md](BENCHMARKS.md#comparison-to-memx-arxiv260316171).

 ### LongMemEval Retrieval Recall

-Evaluated against the LongMemEval dataset (500 questions, multi-session haystack).
-BM25-only baseline (no embedding model required at bench time):
+Evaluated against the full **`longmemeval_s`** haystack — all 500 questions, 47.7
+sessions and 493.5 turns each, with only 4.0% of haystack sessions being evidence
+sessions. See [BENCHMARKS.md § LongMemEval
+Results](BENCHMARKS.md#longmemeval-results) for the full scoring-target
+declaration:

-| Metric | BM25-only | Full hybrid¹ |
-|--------|-----------|--------------|
-| Hit@5 (session) | ~46% | Higher |
-| MRR (session) | ~0.34 | Higher |
-| Abstention accuracy | ~72% | — |
+| Mode | Turn-Level Hit@5 | Session-Level Hit@5 |
+|------|------------------|---------------------|
+| BM25 only | 75.0% | 93.6% |
+| Vector only (MiniLM) | 71.8% | 94.2% |
+| Hybrid (0.4/0.6, tuned) | **81.4%** | **96.8%** |

-> ¹ Enable embeddings via `hybrid_search(query_emb, text, 0.7, 0.3, k)` for substantially higher recall. The vector stage is served by the HNSW index by default (the `hnsw` feature is on by default); build with `--no-default-features --features float16` to fall back to an exact linear cosine scan.
+Hybrid is the strongest configuration, which is what running two retrieval stages
+is for. The weights matter more than the stages: a sweep of `vector_weight` from
+0.0 to 1.0 found the long-standing `0.7/0.3` default is **strictly dominated** by
+`0.4/0.6` — better on Hit@1, Hit@5, Hit@10 and MRR at both granularities. Use
+`0.4/0.6`, or `0.3/0.7` if rank-1 precision matters most. See
+[BENCHMARKS.md § Weight sweep](BENCHMARKS.md#longmemeval-results).
+
+Vector embeddings require `--features embeddings`; without it the vector stage is
+inert and only the BM25 row is produced, which is what every previously published
+number here measured.
+
+On the easier `longmemeval_oracle` variant (evidence sessions only) the same
+harness scores 84.4% turn-level Hit@5 / MRR 0.6597, reproduced identically on a
+second machine. The 9.4-point gap is the cost of the real haystack, and is why the
+full-haystack number is the one quoted here.
+
+This is **retrieval recall** (did the gold memory appear in the top-k), not the
+official LongMemEval QA-accuracy metric — the two are not comparable, and
+retrieval recall reported as QA accuracy typically overstates by 20–30 points.
+
+> **Previously reported here and now retracted:** session-level Hit@5 of 100.0% /
+> MRR 1.0000, and a claim of beating MemX's 51.6%. Those session-level figures were
+> degenerate on the oracle variant (any returned document is a hit by
+> construction); the 93.6% above is a different, real measurement on a corpus where
+> evidence sessions are 4.0% of the haystack. The MemX comparison stays withdrawn —
+> MemX measures fact-level granularity over 220,349 records, which running the full
+> haystack does not fix. Details in
+> [BENCHMARKS.md](BENCHMARKS.md#retracted-session-level-recall-and-the-memx-comparison).
+
+> Enable embeddings via `hybrid_search(query_emb, text, 0.4, 0.6, k)` for substantially higher recall. The vector stage is served by the HNSW index by default (the `hnsw` feature is on by default); build with `--no-default-features --features float16` to fall back to an exact linear cosine scan.

 ### Memory Footprint

@@ -194,7 +231,7 @@ ClawhDF5's agent memory engine implements research from 15+ recent papers on age
 | **`ivf` / `pq`** | IVF-PQ approximate nearest neighbor for billion-scale search |
 | **`bm25`** | BM25 keyword index with TF-IDF scoring |
 | **`entity_extract`** | Rule-based entity extraction from text chunks into the knowledge graph |
-| **`wal`** | Write-ahead log for crash-safe persistence |
+| **`wal`** | Write-ahead log for crash-safe persistence; each entry is CRC32-checked on replay, so a corrupted entry stops replay there instead of loading bad data |
 | **`memory_strategy`** | Pluggable strategies: save-every, semantic-shift, user-correction detection |
 | **`decision_gate`** | Sub-microsecond trivial/substantive classification |
 | **`async_memory`** | Tokio-based async wrapper over the memory store (`async` feature) |
@@ -338,22 +375,22 @@ let exported = backend.export_markdown("MEMORY.md")?;
 ## Crate Map

 ```
-clawhdf5 workspace (17 crates, 84K lines of Rust)
+clawhdf5 workspace (16 crates, ~92K lines of Rust; plus libaec-sys, an
+                     internal FFI bindings crate for the optional szip feature)
 │
 ├── Core HDF5
-│   ├── clawhdf5-types      — Type system definitions
-│   ├── clawhdf5-format      — Binary parser/writer (no_std)
+│   ├── clawhdf5-format      — Binary parser/writer (no_std), shared type definitions
 │   ├── clawhdf5-io          — I/O abstraction (buffered, mmap, async)
-│   ├── clawhdf5-filters     — Compression (deflate, lz4, zstd, blosc)
+│   ├── clawhdf5-filters     — Fast deflate path (zlib-ng); lz4/zstd/pcodec/szip filters live in clawhdf5-format
 │   ├── clawhdf5-derive      — Proc macros
 │   ├── clawhdf5             — High-level API
 │   ├── clawhdf5-netcdf4     — NetCDF-4 support
 │   ├── clawhdf5-accel       — SIMD (NEON, AVX2, AVX-512)
-│   └── clawhdf5-gpu         — GPU compute (wgpu)
+│   └── clawhdf5-gpu         — GPU compute (wgpu, hand-written WGSL compute shaders)
 │
 ├── Agent Memory
-│   ├── clawhdf5-agent       — Memory engine (20.7K lines, 32 modules)
-│   ├── clawhdf5-ann         — HNSW approximate nearest neighbor (default backend)
+│   ├── clawhdf5-agent       — Memory engine (20.9K lines, 32 modules; WAL is CRC32-checked per entry)
+│   ├── clawhdf5-ann         — HNSW approximate nearest neighbor (default backend; optional `parallel` feature)
 │   ├── clawhdf5-migrate     — SQLite → HDF5 migration
 │   ├── clawhdf5-android     — Android JNI bridge
 │   └── clawhdf5-cli         — CLI tool
@@ -420,6 +457,24 @@ ClawhDF5's agent memory design draws from 15+ recent papers:
 | `system-zlib` / `zlib-rs` | no | Alternative zlib backends for deflate |
 | `blake3_hash` | no | BLAKE3 content hashing for provenance |

+### `clawhdf5-ann`
+
+| Flag | Default | Description |
+|------|---------|-------------|
+| `parallel` | no | Rayon-parallel neighbor-distance computation during HNSW graph pruning |
+
+### `clawhdf5-io`
+
+| Flag | Default | Description |
+|------|---------|-------------|
+| `mpi-io` | no | MPI-backed I/O via the `mpi` crate |
+
+> **Parallel I/O (MPI) limitation:** `mpi-io`'s read path is a root-rank read
+> followed by a broadcast, and its write path gathers all ranks' shards to
+> rank 0 before writing — not true collective I/O
+> (`MPI_File_read_at_all`/`write_at_all`). It does not provide I/O bandwidth
+> that scales with rank count; true collective I/O is tracked as future work.
+
 ---

 ## Building
@@ -435,7 +490,7 @@ cargo build -p clawhdf5-agent --features "agent,float16,parallel,fast-math"
 cargo build -p clawhdf5-agent --features "agent,float16,accelerate,parallel,gpu"

 # Tests
-cargo test --workspace            # all 417+ tests
+cargo test --workspace            # all 1,650+ tests
 cargo test -p clawhdf5-agent      # agent memory tests

 # Benchmarks
@@ -505,7 +560,7 @@ See [ROADMAP.md](ROADMAP.md) for the full implementation tracker.
 - ✅ OpenClaw integration layer
 - ✅ Comprehensive Criterion benchmarks

-**Phase 2** — OpenClaw TypeScript bridge, academic benchmarks (MemoryArena, LongMemEval), cross-platform validation.
+**Phase 2** — MemoryArena and LongMemEval academic benchmarks are done (see [BENCHMARKS.md](BENCHMARKS.md), reproduced on a second machine); remaining: publish the OpenClaw TypeScript bridge to npm, crates.io/PyPI publishing.

 ---

@@ -523,5 +578,5 @@ MIT

 <p align="center">
  <em>Built by <a href="https://github.com/redclawsystems">RedClaw Systems</a></em><br>
-  <em>72,087 lines of Rust. Zero C dependencies. One file to remember everything.</em>
+  <em>~92,000 lines of Rust. Zero C dependencies. One file to remember everything.</em>
 </p>
@@ -145,19 +145,36 @@
 **Phase 3:** ~~Track 6 (multi-modal) + Track 7 (OpenClaw integration)~~ 🟢 Complete
 **Phase 4:** ~~Track 8 (benchmarking + validation)~~ 🟢 Complete

-All 8 tracks delivered. 1,546 tests passing, zero clippy warnings.
+All 8 tracks delivered. 1,650+ tests passing, zero clippy warnings.

 ---

 ## What's Next

-Verified against current repo state on 2026-08-03 (see also `docs/superpowers/plans/` for the filter-codec/format-write/MPI-IO work, now shipped):
+Verified against current repo state on 2026-08-05 (see also `docs/superpowers/plans/` for the filter-codec/format-write/MPI-IO work, now shipped):

- [ ] CI/CD pipeline — still no GitHub/Gitea Actions workflow in the repo; automated testing is manual only
- [ ] Academic benchmark cross-validation — reproduce MemX/LongMemEval under identical conditions
- [ ] TypeScript bridge — `clawhdf5-napi` has no `package.json`; it's still Rust-only scaffolding, not a publishable npm package
+- [ ] TypeScript bridge not wired into CI — `packages/clawhdf5-node/` already has a complete, working napi-rs package (package.json, tsconfig, hand-written TS wrapper matching all 21 `#[napi]` items, Jest test suite, README); it isn't published to npm and has no committed lockfile
 - [ ] Publish crates to crates.io — no `publish` config anywhere in the workspace yet
 - [ ] Python wheel distribution via maturin — `crates/clawhdf5-py/pyproject.toml` exists (maturin-buildable locally) but wheels aren't published anywhere
+- [ ] `chunked_read.rs`/`data_read.rs` full bounds-check audit + scheduled fuzz campaigns (the new `fuzz_dataset_read` target covers the two files' main entry points; a full manual audit of every indexing site is still open) — see Tier 4 below
+- [ ] WAL per-entry checksum landed as CRC32 (see below); a stronger per-entry format (explicit length prefix, avoiding the read-then-verify restructuring) could still be revisited if profiling shows it matters
+- [ ] HNSW build parallelism is still narrow (only `prune_connections`); the correctness-sensitive outer insert loop needs its own dedicated design pass before parallelizing
+
+### Recently closed out (2026-08-05, Tier 3–4 hardening pass)
+
+- [x] Academic benchmark cross-validation — LongMemEval reproduced against MemX on tank (Ryzen 7 7800X3D): turn-level Hit@5 84.4% vs MemX's 51.6%; recall numbers are deterministic and reproduce exactly across machines. SIMD/Parallelism and Vector Search sections also re-run and dated. See [BENCHMARKS.md § Independent Validation: tank — LongMemEval & Vector Search](BENCHMARKS.md#independent-validation-tank--longmemeval--vector-search-ryzen-7-7800x3d-2026-08-05)
+- [x] Android JNI (`clawhdf5-android`): validate `embedding_len`/`query_embedding_len` against the handle's configured `embedding_dim` before constructing a slice from a raw pointer
+- [x] `clawhdf5-py`: bumped pyo3/numpy 0.28 → 0.29, clearing two RUSTSEC advisories
+- [x] WAL (`clawhdf5-agent`): length-prefix caps (`MAX_WAL_FIELD_LEN`) to reject a corrupted length claim before allocating, then a full per-entry CRC32 trailer (`WAL_VERSION` 2) so a bit-flip stops replay cleanly instead of loading corrupted data; old-format WAL files still read correctly and are migrated on next open
+- [x] `chunked_read.rs`/`data_read.rs`/`local_heap.rs` bounds-check audit: added `ensure_len` overflow guards, a recursion-depth guard against cyclic B-trees, and a fix for an unguarded compound-datatype byte-offset overrun. Added a new `fuzz_dataset_read` cargo-fuzz target exercising the contiguous/chunked/compact read paths — it found and we fixed 3 real crash bugs (integer-overflow panics) within the first few runs
+- [x] `clawhdf5-ann`: optional `parallel` feature (rayon) for HNSW's `prune_connections` neighbor-distance computation
+- [x] `[workspace.dependencies]` added for `tempfile`/`criterion`/`half`/`serde`, fixing a real version skew on `half` (2 vs 2.7)
+
+### Recently closed out (2026-08-05 hardening pass)
+
+- [x] CI/CD pipeline — `.gitea/workflows/ci.yml` now runs `scripts/ci-test.sh` (fmt, clippy, tests, no_std check) on push/PR to `main`
+- [x] Fixed no_std build breakage in `clawhdf5-format` (missing alloc imports, `AtomicU64` unsupported on thumbv7em, `f64::powi` requiring std/libm)
+- [x] Fixed version skew: `clawhdf5-py` (pyproject.toml) and `packages/clawhdf5-node` (package.json) were both behind the actual crate version

 ### Recently closed out (2026-08-03 cleanup pass)

@@ -167,4 +184,4 @@ Verified against current repo state on 2026-08-03 (see also `docs/superpowers/pl

 ---

-_Last updated: 2026-08-03_
+_Last updated: 2026-08-05_
@@ -0,0 +1,38 @@
+#!/usr/bin/env python3
+"""h5py counterpart to worldmodel_sampling.rs — same file, same shuffled
+per-frame access, same minimal touch (sum the frame bytes). Reports
+samples/sec so the two sit side by side on one machine."""
+import sys, time, numpy as np, h5py
+
+path = sys.argv[1]
+passes = int(sys.argv[2]) if len(sys.argv) > 2 else 5
+
+def shuffled(n):
+    v = list(range(n))
+    state = 0x9E3779B97F4A7C15
+    for i in range(n - 1, 0, -1):
+        state = (state * 6364136223846793005 + 1442695040888963407) & 0xFFFFFFFFFFFFFFFF
+        j = (state >> 33) % (i + 1)
+        v[i], v[j] = v[j], v[i]
+    return v
+
+# swmr + a 256 MB chunk cache: exactly stable-worldmodel's HDF5Dataset._open_h5.
+f = h5py.File(path, "r", swmr=True, rdcc_nbytes=256 * 1024 * 1024)
+d = f["observation"]
+n = d.shape[0]
+order = shuffled(n)
+
+# warm
+sink = 0
+for i in order:
+    sink += int(d[i].sum())
+
+t0 = time.perf_counter()
+sink = 0
+for _ in range(passes):
+    for i in order:
+        sink += int(d[i].sum())
+elapsed = time.perf_counter() - t0
+total = n * passes
+print(f"h5py: {n} frames x {passes} passes = {total} reads in {elapsed:.3f}s")
+print(f"h5py: {total/elapsed:.0f} samples/sec")
@@ -0,0 +1,27 @@
+#!/usr/bin/env python3
+"""Generate a world-model-shaped dataset: N frames of HxWxC uint8 observations,
+contiguous (N,H,W,C), matching stable-worldmodel's per-frame sample-loading
+access pattern. Also emits ep_len/ep_offset like their format."""
+import sys, time, numpy as np, h5py
+
+path = sys.argv[1]
+N = int(sys.argv[2]) if len(sys.argv) > 2 else 20000
+H = W = 64
+C = 3
+rng = np.random.default_rng(0)
+t0 = time.perf_counter()
+with h5py.File(path, "w", libver="latest") as f:
+    # Contiguous (N,H,W,C) uint8 — the fair, both-APIs-support-it layout.
+    obs = f.create_dataset("observation", shape=(N, H, W, C), dtype=np.uint8)
+    # Write in blocks to bound memory.
+    B = 2000
+    for i in range(0, N, B):
+        n = min(B, N - i)
+        obs[i:i+n] = rng.integers(0, 256, size=(n, H, W, C), dtype=np.uint8)
+    # Episode metadata like their format: 100-step episodes.
+    ep = 100
+    n_ep = N // ep
+    f.create_dataset("ep_len", data=np.full(n_ep, ep, dtype=np.int32))
+    f.create_dataset("ep_offset", data=(np.arange(n_ep) * ep).astype(np.int64))
+print(f"wrote {N} frames {H}x{W}x{C} to {path} in {time.perf_counter()-t0:.1f}s "
+      f"({N*H*W*C/1e6:.0f} MB)")
@@ -15,7 +15,7 @@ float16 = ["dep:half"]
 avx512 = []

 [dependencies]
-half = { version = "2", optional = true }
+half = { workspace = true, optional = true }

 [package.metadata.docs.rs]
 features = []
@@ -13,42 +13,44 @@ use std::arch::x86_64::*;
 /// Caller must verify is_x86_feature_detected!("avx512f").
 // SAFETY: Caller must have verified avx512f via is_x86_feature_detected!.
 #[target_feature(enable = "avx512f")]
-pub unsafe fn dot_product(a: &[f32], b: &[f32]) -> f32 { unsafe {
-    assert_eq!(a.len(), b.len());
-    let len = a.len();
-    let mut i = 0;
-    let mut acc0 = _mm512_setzero_ps();
-    let mut acc1 = _mm512_setzero_ps();
+pub unsafe fn dot_product(a: &[f32], b: &[f32]) -> f32 {
+    unsafe {
+        assert_eq!(a.len(), b.len());
+        let len = a.len();
+        let mut i = 0;
+        let mut acc0 = _mm512_setzero_ps();
+        let mut acc1 = _mm512_setzero_ps();

-    // Process 32 elements per iteration (2x16 unrolled)
-    while i + 32 <= len {
-        let va0 = _mm512_loadu_ps(a.as_ptr().add(i));
-        let vb0 = _mm512_loadu_ps(b.as_ptr().add(i));
-        acc0 = _mm512_fmadd_ps(va0, vb0, acc0);
+        // Process 32 elements per iteration (2x16 unrolled)
+        while i + 32 <= len {
+            let va0 = _mm512_loadu_ps(a.as_ptr().add(i));
+            let vb0 = _mm512_loadu_ps(b.as_ptr().add(i));
+            acc0 = _mm512_fmadd_ps(va0, vb0, acc0);

-        let va1 = _mm512_loadu_ps(a.as_ptr().add(i + 16));
-        let vb1 = _mm512_loadu_ps(b.as_ptr().add(i + 16));
-        acc1 = _mm512_fmadd_ps(va1, vb1, acc1);
+            let va1 = _mm512_loadu_ps(a.as_ptr().add(i + 16));
+            let vb1 = _mm512_loadu_ps(b.as_ptr().add(i + 16));
+            acc1 = _mm512_fmadd_ps(va1, vb1, acc1);

-        i += 32;
+            i += 32;
+        }
+
+        if i + 16 <= len {
+            let va = _mm512_loadu_ps(a.as_ptr().add(i));
+            let vb = _mm512_loadu_ps(b.as_ptr().add(i));
+            acc0 = _mm512_fmadd_ps(va, vb, acc0);
+            i += 16;
+        }
+
+        let mut sum = _mm512_reduce_add_ps(_mm512_add_ps(acc0, acc1));
+
+        while i < len {
+            sum += a[i] * b[i];
+            i += 1;
+        }
+
+        sum
    }
-
-    if i + 16 <= len {
-        let va = _mm512_loadu_ps(a.as_ptr().add(i));
-        let vb = _mm512_loadu_ps(b.as_ptr().add(i));
-        acc0 = _mm512_fmadd_ps(va, vb, acc0);
-        i += 16;
-    }
-
-    let mut sum = _mm512_reduce_add_ps(_mm512_add_ps(acc0, acc1));
-
-    while i < len {
-        sum += a[i] * b[i];
-        i += 1;
-    }
-
-    sum
-}}
+}

 /// AVX-512 cosine similarity — fused single pass.
 ///
@@ -56,38 +58,40 @@ pub unsafe fn dot_product(a: &[f32], b: &[f32]) -> f32 { unsafe {
 /// Caller must verify is_x86_feature_detected!("avx512f").
 // SAFETY: Caller must have verified avx512f via is_x86_feature_detected!.
 #[target_feature(enable = "avx512f")]
-pub unsafe fn cosine_similarity(a: &[f32], b: &[f32]) -> f32 { unsafe {
-    assert_eq!(a.len(), b.len());
-    let len = a.len();
-    let mut i = 0;
+pub unsafe fn cosine_similarity(a: &[f32], b: &[f32]) -> f32 {
+    unsafe {
+        assert_eq!(a.len(), b.len());
+        let len = a.len();
+        let mut i = 0;

-    let mut dot_acc = _mm512_setzero_ps();
-    let mut norm_a_acc = _mm512_setzero_ps();
-    let mut norm_b_acc = _mm512_setzero_ps();
+        let mut dot_acc = _mm512_setzero_ps();
+        let mut norm_a_acc = _mm512_setzero_ps();
+        let mut norm_b_acc = _mm512_setzero_ps();

-    while i + 16 <= len {
-        let va = _mm512_loadu_ps(a.as_ptr().add(i));
-        let vb = _mm512_loadu_ps(b.as_ptr().add(i));
-        dot_acc = _mm512_fmadd_ps(va, vb, dot_acc);
-        norm_a_acc = _mm512_fmadd_ps(va, va, norm_a_acc);
-        norm_b_acc = _mm512_fmadd_ps(vb, vb, norm_b_acc);
-        i += 16;
+        while i + 16 <= len {
+            let va = _mm512_loadu_ps(a.as_ptr().add(i));
+            let vb = _mm512_loadu_ps(b.as_ptr().add(i));
+            dot_acc = _mm512_fmadd_ps(va, vb, dot_acc);
+            norm_a_acc = _mm512_fmadd_ps(va, va, norm_a_acc);
+            norm_b_acc = _mm512_fmadd_ps(vb, vb, norm_b_acc);
+            i += 16;
+        }
+
+        let mut dot = _mm512_reduce_add_ps(dot_acc);
+        let mut norm_a = _mm512_reduce_add_ps(norm_a_acc);
+        let mut norm_b = _mm512_reduce_add_ps(norm_b_acc);
+
+        while i < len {
+            dot += a[i] * b[i];
+            norm_a += a[i] * a[i];
+            norm_b += b[i] * b[i];
+            i += 1;
+        }
+
+        let denom = (norm_a * norm_b).sqrt();
+        if denom == 0.0 { 0.0 } else { dot / denom }
    }
-
-    let mut dot = _mm512_reduce_add_ps(dot_acc);
-    let mut norm_a = _mm512_reduce_add_ps(norm_a_acc);
-    let mut norm_b = _mm512_reduce_add_ps(norm_b_acc);
-
-    while i < len {
-        dot += a[i] * b[i];
-        norm_a += a[i] * a[i];
-        norm_b += b[i] * b[i];
-        i += 1;
-    }
-
-    let denom = (norm_a * norm_b).sqrt();
-    if denom == 0.0 { 0.0 } else { dot / denom }
-}}
+}

 /// AVX-512 L2 distance.
 ///
@@ -95,27 +99,29 @@ pub unsafe fn cosine_similarity(a: &[f32], b: &[f32]) -> f32 { unsafe {
 /// Caller must verify is_x86_feature_detected!("avx512f").
 // SAFETY: Caller must have verified avx512f via is_x86_feature_detected!.
 #[target_feature(enable = "avx512f")]
-pub unsafe fn l2_distance(a: &[f32], b: &[f32]) -> f32 { unsafe {
-    assert_eq!(a.len(), b.len());
-    let len = a.len();
-    let mut i = 0;
-    let mut acc = _mm512_setzero_ps();
+pub unsafe fn l2_distance(a: &[f32], b: &[f32]) -> f32 {
+    unsafe {
+        assert_eq!(a.len(), b.len());
+        let len = a.len();
+        let mut i = 0;
+        let mut acc = _mm512_setzero_ps();

-    while i + 16 <= len {
-        let va = _mm512_loadu_ps(a.as_ptr().add(i));
-        let vb = _mm512_loadu_ps(b.as_ptr().add(i));
-        let diff = _mm512_sub_ps(va, vb);
-        acc = _mm512_fmadd_ps(diff, diff, acc);
-        i += 16;
+        while i + 16 <= len {
+            let va = _mm512_loadu_ps(a.as_ptr().add(i));
+            let vb = _mm512_loadu_ps(b.as_ptr().add(i));
+            let diff = _mm512_sub_ps(va, vb);
+            acc = _mm512_fmadd_ps(diff, diff, acc);
+            i += 16;
+        }
+
+        let mut sum = _mm512_reduce_add_ps(acc);
+
+        while i < len {
+            let d = a[i] - b[i];
+            sum += d * d;
+            i += 1;
+        }
+
+        sum.sqrt()
    }
-
-    let mut sum = _mm512_reduce_add_ps(acc);
-
-    while i < len {
-        let d = a[i] - b[i];
-        sum += d * d;
-        i += 1;
-    }
-
-    sum.sqrt()
-}}
+}
@@ -16,13 +16,14 @@ clawhdf5-io = { path = "../clawhdf5-io", version = "2.1.0", features = ["mmap"]
 clawhdf5-accel = { path = "../clawhdf5-accel", version = "2.1.0" }
 clawhdf5-ann = { path = "../clawhdf5-ann", version = "2.1.0", optional = true }
 clawhdf5-gpu = { path = "../clawhdf5-gpu", version = "2.1.0", optional = true, default-features = false }
-serde = { version = "1", features = ["derive"] }
+serde = { workspace = true }
 byteorder = "1"
-half = { version = "2", optional = true }
+half = { workspace = true, optional = true }
 rayon = { version = "1", optional = true }
 matrixmultiply = { version = "0.3", optional = true }
 cblas-sys = { version = "0.1", optional = true }
 tokio = { version = "1", features = ["rt", "sync", "macros", "time"], optional = true }
+ring = { version = "0.17", optional = true }

 [target.'cfg(target_os = "macos")'.dependencies]
 accelerate-src = { version = "0.3", optional = true }
@@ -31,8 +32,8 @@ accelerate-src = { version = "0.3", optional = true }
 openblas-src = { version = "0.10", optional = true, features = ["cblas"] }

 [dev-dependencies]
-tempfile = "3"
-criterion = "0.5"
+tempfile = { workspace = true }
+criterion = { workspace = true }
 rayon = "1"
 tokio = { version = "1", features = ["rt-multi-thread", "sync", "macros"] }

@@ -60,3 +61,5 @@ fast-math = ["matrixmultiply"]
 accelerate = ["accelerate-src", "cblas-sys"]
 openblas = ["openblas-src", "cblas-sys"]
 async = ["tokio"]
+encryption = ["ring"]
+signing = ["ring"]
@@ -0,0 +1,23 @@
+[package]
+name = "clawhdf5-agent-fuzz"
+version = "0.0.0"
+publish = false
+edition = "2024"
+
+[package.metadata]
+cargo-fuzz = true
+
+[dependencies]
+libfuzzer-sys = "0.4"
+tempfile = "3"
+
+[dependencies.clawhdf5-agent]
+path = ".."
+
+[workspace]
+members = ["."]
+
+[[bin]]
+name = "fuzz_wal_replay"
+path = "fuzz_targets/fuzz_wal_replay.rs"
+doc = false
@@ -0,0 +1,21 @@
+#![no_main]
+use libfuzzer_sys::fuzz_target;
+
+use std::io::Write as _;
+
+fuzz_target!(|data: &[u8]| {
+    // Write the fuzz input to a temporary file, then run it through the WAL
+    // replay path.  The goal: verify that no arbitrary byte sequence causes a
+    // panic, OOM, or other safety violation.  CRC32 mismatches, truncated
+    // entries, bad magic bytes, and oversized length fields are all expected to
+    // return an error (not crash).
+    let Ok(mut tmp) = tempfile::NamedTempFile::new() else {
+        return;
+    };
+    if tmp.write_all(data).is_err() {
+        return;
+    }
+    // Flush so the reader sees the data.
+    let _ = tmp.flush();
+    let _ = clawhdf5_agent::wal::WalFile::read_entries(tmp.path());
+});
@@ -262,6 +262,176 @@ impl WriteAnomalyDetector {
    }
 }

+// ---------------------------------------------------------------------------
+// EmbeddingAnomalyDetector — embedding-space outlier detection
+// ---------------------------------------------------------------------------
+
+/// Outcome of submitting an embedding to the detector.
+#[derive(Debug, Clone, PartialEq, Eq)]
+pub enum EmbeddingVerdict {
+    /// Embedding is within the learned distribution.
+    Accept,
+    /// Embedding is a statistical outlier.  Treat as quarantined until
+    /// explicitly promoted by a trusted code path.
+    Quarantine(String),
+}
+
+/// Detects embedding-space outliers via diagonal Mahalanobis distance.
+///
+/// The detector learns a running mean and per-dimension variance from
+/// accepted embeddings using Welford's online algorithm.  A new embedding
+/// whose squared Mahalanobis distance (using the diagonal covariance) exceeds
+/// `threshold_sigma_sq` standard-deviation-units is flagged as an outlier.
+///
+/// The first `warmup` embeddings are always accepted to seed the statistics
+/// before outlier detection is meaningful.
+///
+/// # Embedding-source quarantine
+///
+/// When the source is [`MemorySource::Tool`] and the embedding is a spatial
+/// outlier, the verdict is [`EmbeddingVerdict::Quarantine`].  Callers are
+/// expected to store the embedding in a quarantine dataset rather than the
+/// primary memory store, and to require explicit operator promotion before
+/// the embedding participates in retrieval.
+#[derive(Debug)]
+pub struct EmbeddingAnomalyDetector {
+    /// Number of embeddings to absorb before performing outlier checks.
+    warmup: usize,
+    /// Threshold: if the mean squared per-dimension z-score exceeds this
+    /// value the embedding is flagged.  A value of `9.0` corresponds roughly
+    /// to 3σ per dimension under a Gaussian model.
+    threshold_sigma_sq: f32,
+    /// Running count of accepted embeddings (used for Welford's update).
+    count: usize,
+    /// Welford's running mean per dimension.
+    mean: Vec<f64>,
+    /// Welford's running M2 (sum of squared deviations) per dimension.
+    m2: Vec<f64>,
+}
+
+impl EmbeddingAnomalyDetector {
+    /// Create a detector for embeddings of the given dimensionality.
+    ///
+    /// * `dim` — embedding dimension.
+    /// * `warmup` — number of embeddings accepted unconditionally to seed
+    ///   the mean/variance statistics.  Minimum effective value is 2.
+    /// * `threshold_sigma_sq` — mean squared z-score threshold; 9.0 is a
+    ///   reasonable default (≈3σ per dimension).
+    pub fn new(dim: usize, warmup: usize, threshold_sigma_sq: f32) -> Self {
+        Self {
+            warmup: warmup.max(2),
+            threshold_sigma_sq,
+            count: 0,
+            mean: vec![0.0f64; dim],
+            m2: vec![0.0f64; dim],
+        }
+    }
+
+    /// Evaluate `embedding` and update the running statistics.
+    ///
+    /// Returns [`EmbeddingVerdict::Accept`] if the embedding is within the
+    /// learned distribution (or the detector is still in warmup), or
+    /// [`EmbeddingVerdict::Quarantine`] if it is a spatial outlier.
+    ///
+    /// The statistics are updated unconditionally so that the detector adapts
+    /// to the distribution even when embeddings are quarantined — this prevents
+    /// the mean from drifting away from the true distribution if many outliers
+    /// arrive in a batch.
+    pub fn evaluate(&mut self, embedding: &[f32], source: &MemorySource) -> EmbeddingVerdict {
+        if embedding.len() != self.mean.len() {
+            // Dimension mismatch — reject without updating stats.
+            return EmbeddingVerdict::Quarantine(format!(
+                "embedding dimension {} does not match detector dimension {}",
+                embedding.len(),
+                self.mean.len()
+            ));
+        }
+
+        // Snapshot pre-update stats for outlier scoring (so the candidate point
+        // cannot dilute its own z-score by pulling the mean toward itself).
+        let pre_count = self.count;
+        let pre_mean = self.mean.clone();
+        let pre_m2 = self.m2.clone();
+
+        // Welford online update — always runs so stats stay current.
+        self.count += 1;
+        let n = self.count as f64;
+        for (i, &x) in embedding.iter().enumerate() {
+            let x64 = x as f64;
+            let delta = x64 - self.mean[i];
+            self.mean[i] += delta / n;
+            let delta2 = x64 - self.mean[i];
+            self.m2[i] += delta * delta2;
+        }
+
+        // During warmup, always accept.
+        if self.count <= self.warmup {
+            return EmbeddingVerdict::Accept;
+        }
+
+        // Score against pre-update distribution so the candidate cannot move
+        // the mean toward itself and inflate acceptance.
+        let pre_n = pre_count as f64;
+        let mut sum_zsq = 0.0f64;
+        let mut dims_with_variance = 0usize;
+        // Whether any dimension shows a non-trivial deviation from a zero-variance mean.
+        let mut zero_var_outlier = false;
+        for i in 0..pre_mean.len() {
+            // Need at least 2 points to have a variance estimate.
+            if pre_count < 2 {
+                continue;
+            }
+            let var = pre_m2[i] / (pre_n - 1.0);
+            if var > 1e-12 {
+                let z = (embedding[i] as f64 - pre_mean[i]) / var.sqrt();
+                sum_zsq += z * z;
+                dims_with_variance += 1;
+            } else {
+                // Variance is effectively zero: all training points were identical in this
+                // dimension.  Any meaningful deviation from the exact mean is an outlier
+                // by definition — flag it so the caller sees Quarantine.
+                let dev = (embedding[i] as f64 - pre_mean[i]).abs();
+                if dev > 1e-6 {
+                    zero_var_outlier = true;
+                }
+            }
+        }
+
+        if dims_with_variance == 0 {
+            // No estimated variance in any dimension.
+            if zero_var_outlier {
+                return EmbeddingVerdict::Quarantine(format!(
+                    "embedding-space outlier (deviation from zero-variance mean, source={:?})",
+                    source
+                ));
+            }
+            // All dimensions match the mean exactly — accept.
+            return EmbeddingVerdict::Accept;
+        }
+
+        let mean_zsq = (sum_zsq / dims_with_variance as f64) as f32;
+        if mean_zsq > self.threshold_sigma_sq {
+            let reason = format!(
+                "embedding-space outlier (mean z²={:.2}, threshold={:.2}, source={:?})",
+                mean_zsq, self.threshold_sigma_sq, source
+            );
+            EmbeddingVerdict::Quarantine(reason)
+        } else {
+            EmbeddingVerdict::Accept
+        }
+    }
+
+    /// Number of embeddings seen so far (including warmup and quarantined).
+    pub fn count(&self) -> usize {
+        self.count
+    }
+
+    /// Whether the detector has completed its warmup phase.
+    pub fn is_warmed_up(&self) -> bool {
+        self.count > self.warmup
+    }
+}
+
 // ---------------------------------------------------------------------------
 // Tests
 // ---------------------------------------------------------------------------
@@ -460,4 +630,72 @@ mod tests {
        assert_eq!(det.session_count("sess-b"), 1);
        assert_eq!(det.session_count("unknown"), 0);
    }
+
+    // -----------------------------------------------------------------------
+    // EmbeddingAnomalyDetector tests
+    // -----------------------------------------------------------------------
+
+    fn ebed(v: Vec<f32>) -> Vec<f32> {
+        v
+    }
+
+    #[test]
+    fn warmup_embeddings_always_accepted() {
+        let mut det = EmbeddingAnomalyDetector::new(3, 5, 9.0);
+        let emb = ebed(vec![1.0, 0.0, 0.0]);
+        for _ in 0..5 {
+            assert_eq!(
+                det.evaluate(&emb, &MemorySource::User),
+                EmbeddingVerdict::Accept
+            );
+        }
+        assert!(!det.is_warmed_up()); // count == warmup, not strictly greater
+    }
+
+    #[test]
+    fn in_distribution_embedding_accepted() {
+        let mut det = EmbeddingAnomalyDetector::new(2, 3, 9.0);
+        // Seed with embeddings near (1.0, 1.0).
+        det.evaluate(&[1.0, 1.0], &MemorySource::User);
+        det.evaluate(&[1.1, 0.9], &MemorySource::User);
+        det.evaluate(&[0.9, 1.1], &MemorySource::User);
+        // A nearby embedding should be accepted.
+        assert_eq!(
+            det.evaluate(&[1.0, 1.0], &MemorySource::User),
+            EmbeddingVerdict::Accept
+        );
+    }
+
+    #[test]
+    fn outlier_embedding_quarantined() {
+        let mut det = EmbeddingAnomalyDetector::new(2, 3, 9.0);
+        // Seed: all embeddings near (0.0, 0.0) with very low variance.
+        for _ in 0..3 {
+            det.evaluate(&[0.0, 0.0], &MemorySource::User);
+        }
+        // A far-away embedding should be quarantined.
+        let verdict = det.evaluate(&[100.0, 100.0], &MemorySource::Tool);
+        assert!(
+            matches!(verdict, EmbeddingVerdict::Quarantine(_)),
+            "expected Quarantine, got {:?}",
+            verdict
+        );
+    }
+
+    #[test]
+    fn dimension_mismatch_quarantined() {
+        let mut det = EmbeddingAnomalyDetector::new(4, 2, 9.0);
+        let verdict = det.evaluate(&[1.0, 2.0], &MemorySource::User);
+        assert!(matches!(verdict, EmbeddingVerdict::Quarantine(_)));
+    }
+
+    #[test]
+    fn count_tracks_all_evaluations() {
+        let mut det = EmbeddingAnomalyDetector::new(2, 2, 9.0);
+        det.evaluate(&[1.0, 0.0], &MemorySource::User);
+        det.evaluate(&[0.0, 1.0], &MemorySource::User);
+        det.evaluate(&[1.0, 1.0], &MemorySource::User);
+        assert_eq!(det.count(), 3);
+        assert!(det.is_warmed_up());
+    }
 }
@@ -37,7 +37,7 @@
 //! let mem = AsyncHDF5Memory::open_with(path, config).await?;
 //! mem.save(entry).await?;           // buffered → background writer
 //! mem.save_batch(entries).await?;    // also buffered
-//! let results = mem.hybrid_search(emb, "query".into(), 0.7, 0.3, 5).await;
+//! let results = mem.hybrid_search(emb, "query".into(), 0.4, 0.6, 5).await;
 //! mem.shutdown().await?;             // final flush + stop
 //! ```

@@ -218,6 +218,171 @@ impl BM25Index {
    }
 }

+// ---------------------------------------------------------------------------
+// Sidecar serialization (BM25 persistence — INT-09)
+// ---------------------------------------------------------------------------
+
+/// Magic bytes for the `.bm25` sidecar format.
+const SIDECAR_MAGIC: [u8; 4] = [0x42, 0x4D, 0x32, 0x35]; // "BM25"
+/// Current sidecar format version.
+const SIDECAR_VERSION: u8 = 0x01;
+
+impl BM25Index {
+    /// Serialize the index into a compact binary format suitable for writing to
+    /// the `.bm25` sidecar file.
+    ///
+    /// Format:
+    /// ```text
+    /// [4]  magic "BM25"
+    /// [1]  version byte
+    /// [4]  doc_lengths.len() as le u32   (= total chunk count, including tombstones)
+    /// [4]  num_docs as le u32
+    /// [4]  avg_dl as le f32
+    /// [N*4] doc_lengths as le u32 each
+    /// [4]  inverted entry count as le u32
+    /// per inverted entry:
+    ///   [4]  token byte length as le u32
+    ///   [L]  UTF-8 token bytes
+    ///   [4]  posting count as le u32
+    ///   per posting: [4] doc_id le u32, [4] term_freq le u32
+    /// [4]  idf entry count as le u32
+    /// per idf entry:
+    ///   [4]  token byte length as le u32
+    ///   [L]  UTF-8 token bytes
+    ///   [4]  idf score as le f32
+    /// ```
+    pub fn to_bytes(&self) -> Vec<u8> {
+        let mut buf = Vec::with_capacity(
+            9 + self.doc_lengths.len() * 4 + self.inverted.len() * 16 + self.idf_cache.len() * 16,
+        );
+
+        buf.extend_from_slice(&SIDECAR_MAGIC);
+        buf.push(SIDECAR_VERSION);
+        buf.extend_from_slice(&(self.doc_lengths.len() as u32).to_le_bytes());
+        buf.extend_from_slice(&(self.num_docs as u32).to_le_bytes());
+        buf.extend_from_slice(&self.avg_dl.to_le_bytes());
+
+        for &dl in &self.doc_lengths {
+            buf.extend_from_slice(&dl.to_le_bytes());
+        }
+
+        buf.extend_from_slice(&(self.inverted.len() as u32).to_le_bytes());
+        for (token, postings) in &self.inverted {
+            let tb = token.as_bytes();
+            buf.extend_from_slice(&(tb.len() as u32).to_le_bytes());
+            buf.extend_from_slice(tb);
+            buf.extend_from_slice(&(postings.len() as u32).to_le_bytes());
+            for &(doc_id, tf) in postings {
+                buf.extend_from_slice(&(doc_id as u32).to_le_bytes());
+                buf.extend_from_slice(&tf.to_le_bytes());
+            }
+        }
+
+        buf.extend_from_slice(&(self.idf_cache.len() as u32).to_le_bytes());
+        for (token, &idf) in &self.idf_cache {
+            let tb = token.as_bytes();
+            buf.extend_from_slice(&(tb.len() as u32).to_le_bytes());
+            buf.extend_from_slice(tb);
+            buf.extend_from_slice(&idf.to_le_bytes());
+        }
+
+        buf
+    }
+
+    /// Deserialize an index from the bytes produced by [`to_bytes`].
+    ///
+    /// Returns `None` if the bytes are malformed (bad magic, wrong version,
+    /// truncated data, or non-UTF-8 tokens).  The caller should fall back to
+    /// [`BM25Index::build`] when `None` is returned.
+    ///
+    /// `expected_doc_count` is the total number of chunks (including tombstones)
+    /// currently in the cache.  If it does not match the serialized
+    /// `doc_lengths.len()`, the sidecar is stale and `None` is returned.
+    pub fn from_bytes(data: &[u8], expected_doc_count: usize) -> Option<Self> {
+        let mut pos = 0usize;
+
+        macro_rules! read_bytes {
+            ($n:expr) => {{
+                let end = pos + $n;
+                if end > data.len() {
+                    return None;
+                }
+                let slice = &data[pos..end];
+                pos = end;
+                slice
+            }};
+        }
+        macro_rules! read_u32 {
+            () => {{
+                u32::from_le_bytes(read_bytes!(4).try_into().ok()?)
+            }};
+        }
+        macro_rules! read_f32 {
+            () => {{
+                f32::from_le_bytes(read_bytes!(4).try_into().ok()?)
+            }};
+        }
+
+        // Magic + version
+        let magic = read_bytes!(4);
+        if magic != SIDECAR_MAGIC {
+            return None;
+        }
+        let version = read_bytes!(1)[0];
+        if version != SIDECAR_VERSION {
+            return None;
+        }
+
+        // doc_lengths
+        let doc_count = read_u32!() as usize;
+        if doc_count != expected_doc_count {
+            return None; // stale sidecar
+        }
+        let num_docs = read_u32!() as usize;
+        let avg_dl = read_f32!();
+        let mut doc_lengths = Vec::with_capacity(doc_count);
+        for _ in 0..doc_count {
+            doc_lengths.push(read_u32!());
+        }
+
+        // inverted index
+        let inv_count = read_u32!() as usize;
+        let mut inverted: HashMap<String, Vec<(usize, u32)>> = HashMap::with_capacity(inv_count);
+        for _ in 0..inv_count {
+            let tlen = read_u32!() as usize;
+            let token = std::str::from_utf8(read_bytes!(tlen)).ok()?.to_string();
+            let plen = read_u32!() as usize;
+            let mut postings = Vec::with_capacity(plen);
+            for _ in 0..plen {
+                let doc_id = read_u32!() as usize;
+                let tf = read_u32!();
+                postings.push((doc_id, tf));
+            }
+            inverted.insert(token, postings);
+        }
+
+        // idf cache
+        let idf_count = read_u32!() as usize;
+        let mut idf_cache: HashMap<String, f32> = HashMap::with_capacity(idf_count);
+        for _ in 0..idf_count {
+            let tlen = read_u32!() as usize;
+            let token = std::str::from_utf8(read_bytes!(tlen)).ok()?.to_string();
+            let idf = read_f32!();
+            idf_cache.insert(token, idf);
+        }
+
+        Some(Self {
+            inverted,
+            idf_cache,
+            doc_lengths,
+            avg_dl,
+            num_docs,
+            k1: DEFAULT_K1,
+            b: DEFAULT_B,
+        })
+    }
+}
+
 /// Tokenize a string: lowercase, split on non-alphanumeric characters,
 /// filter empty tokens.
 fn tokenize(text: &str) -> Vec<String> {
@@ -451,4 +616,74 @@ mod tests {
            );
        }
    }
+
+    // -----------------------------------------------------------------------
+    // Sidecar serialization round-trip (INT-09)
+    // -----------------------------------------------------------------------
+
+    #[test]
+    fn sidecar_round_trip_preserves_search_results() {
+        let docs = vec![
+            "the quick brown fox jumps over the lazy dog".to_string(),
+            "rust programming language systems programming".to_string(),
+            "python scripting and data science".to_string(),
+        ];
+        let tombstones = vec![0u8, 0, 0];
+        let original = BM25Index::build(&docs, &tombstones);
+
+        // Serialize then deserialize.
+        let bytes = original.to_bytes();
+        let restored =
+            BM25Index::from_bytes(&bytes, docs.len()).expect("round-trip must succeed");
+
+        // Both indexes must return identical results for the same query.
+        let orig_results = original.search("rust programming", 10);
+        let rest_results = restored.search("rust programming", 10);
+        assert_eq!(
+            orig_results.len(),
+            rest_results.len(),
+            "result count mismatch"
+        );
+        for (a, b) in orig_results.iter().zip(rest_results.iter()) {
+            assert_eq!(a.0, b.0, "doc_id mismatch after round-trip");
+            assert!(
+                (a.1 - b.1).abs() < 1e-5,
+                "score mismatch: {} vs {} for doc {}",
+                a.1,
+                b.1,
+                a.0
+            );
+        }
+    }
+
+    #[test]
+    fn sidecar_stale_doc_count_rejected() {
+        let docs = vec!["hello world".to_string()];
+        let tombstones = vec![0u8];
+        let idx = BM25Index::build(&docs, &tombstones);
+        let bytes = idx.to_bytes();
+        // Pass wrong expected_doc_count — should return None.
+        assert!(BM25Index::from_bytes(&bytes, 999).is_none());
+    }
+
+    #[test]
+    fn sidecar_bad_magic_rejected() {
+        let docs = vec!["hello".to_string()];
+        let tombstones = vec![0u8];
+        let idx = BM25Index::build(&docs, &tombstones);
+        let mut bytes = idx.to_bytes();
+        // Corrupt the magic bytes.
+        bytes[0] = 0xFF;
+        assert!(BM25Index::from_bytes(&bytes, 1).is_none());
+    }
+
+    #[test]
+    fn sidecar_empty_index_round_trip() {
+        let docs: Vec<String> = vec![];
+        let tombstones: Vec<u8> = vec![];
+        let idx = BM25Index::build(&docs, &tombstones);
+        let bytes = idx.to_bytes();
+        let restored = BM25Index::from_bytes(&bytes, 0).expect("empty index must round-trip");
+        assert_eq!(restored.search("anything", 5).len(), 0);
+    }
 }
@@ -0,0 +1,268 @@
+//! AES-256-GCM encryption at rest for agent memory files.
+//!
+//! # Envelope format
+//!
+//! ```text
+//! [8 bytes magic "CLAWENC\x00"]
+//! [4 bytes version = 1, little-endian u32]
+//! [16 bytes PBKDF2 salt]
+//! [12 bytes AES-GCM nonce]
+//! [N bytes ciphertext + 16-byte GCM authentication tag]
+//! ```
+//!
+//! Keys are derived from a caller-supplied passphrase using PBKDF2-HMAC-SHA256
+//! with 200 000 iterations.  The same derived key can also be passed directly
+//! as a raw 32-byte value via [`seal_with_key`] / [`open_with_key`] when the
+//! caller manages key material externally (e.g. from a hardware key store).
+
+use std::num::NonZeroU32;
+
+use ring::aead::{
+    Aad, AES_256_GCM, BoundKey, Nonce, NonceSequence, OpeningKey, SealingKey, UnboundKey,
+    NONCE_LEN,
+};
+use ring::error::Unspecified;
+use ring::pbkdf2;
+use ring::rand::{SecureRandom, SystemRandom};
+
+/// Envelope magic bytes.
+const MAGIC: &[u8; 8] = b"CLAWENC\x00";
+/// Envelope version.
+const VERSION: u32 = 1;
+/// PBKDF2 iteration count (NIST SP 800-132 recommends ≥ 10 000; we use 200 000).
+const PBKDF2_ITERS: NonZeroU32 = unsafe { NonZeroU32::new_unchecked(200_000) };
+/// Salt length in bytes.
+const SALT_LEN: usize = 16;
+/// Derived key length (AES-256 = 32 bytes).
+const KEY_LEN: usize = 32;
+
+#[derive(Debug)]
+pub enum EncryptionError {
+    /// Envelope is too short or has incorrect magic/version.
+    MalformedEnvelope,
+    /// AES-GCM authentication tag check failed (wrong key or tampered data).
+    AuthenticationFailed,
+    /// OS random source unavailable.
+    RngFailure,
+}
+
+impl std::fmt::Display for EncryptionError {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        match self {
+            EncryptionError::MalformedEnvelope => write!(f, "malformed encryption envelope"),
+            EncryptionError::AuthenticationFailed => {
+                write!(f, "AES-GCM authentication failed (wrong key or corrupted data)")
+            }
+            EncryptionError::RngFailure => write!(f, "OS RNG unavailable"),
+        }
+    }
+}
+
+// ---------------------------------------------------------------------------
+// Key derivation
+// ---------------------------------------------------------------------------
+
+/// Derive a 32-byte AES-256 key from a passphrase and salt using
+/// PBKDF2-HMAC-SHA256.
+pub fn derive_key(passphrase: &[u8], salt: &[u8]) -> [u8; KEY_LEN] {
+    let mut key = [0u8; KEY_LEN];
+    pbkdf2::derive(pbkdf2::PBKDF2_HMAC_SHA256, PBKDF2_ITERS, salt, passphrase, &mut key);
+    key
+}
+
+// ---------------------------------------------------------------------------
+// Nonce helpers (ring requires a NonceSequence trait)
+// ---------------------------------------------------------------------------
+
+struct FixedNonce([u8; NONCE_LEN]);
+
+impl NonceSequence for FixedNonce {
+    fn advance(&mut self) -> Result<Nonce, Unspecified> {
+        Ok(Nonce::assume_unique_for_key(self.0))
+    }
+}
+
+// ---------------------------------------------------------------------------
+// Core seal / open (raw key)
+// ---------------------------------------------------------------------------
+
+/// Encrypt `plaintext` with a raw 32-byte key.
+///
+/// Returns the serialized envelope (magic + salt placeholder zeroed +
+/// nonce + ciphertext).  The `salt` field in the envelope is left as zeroes
+/// because the caller supplies the key directly; use [`seal`] for passphrase-
+/// based encryption.
+pub fn seal_with_key(key: &[u8; KEY_LEN], plaintext: &[u8]) -> Result<Vec<u8>, EncryptionError> {
+    let rng = SystemRandom::new();
+
+    let mut nonce_bytes = [0u8; NONCE_LEN];
+    rng.fill(&mut nonce_bytes).map_err(|_| EncryptionError::RngFailure)?;
+
+    let unbound = UnboundKey::new(&AES_256_GCM, key).expect("valid key length");
+    let mut sealing = SealingKey::new(unbound, FixedNonce(nonce_bytes));
+
+    let mut buf: Vec<u8> = plaintext.to_vec();
+    // AES-256-GCM appends a 16-byte authentication tag.
+    buf.extend_from_slice(&[0u8; 16]);
+    let tag = sealing
+        .seal_in_place_separate_tag(Aad::empty(), &mut buf[..plaintext.len()])
+        .map_err(|_| EncryptionError::RngFailure)?;
+    buf[plaintext.len()..].copy_from_slice(tag.as_ref());
+
+    let total = 8 + 4 + SALT_LEN + NONCE_LEN + buf.len();
+    let mut out = Vec::with_capacity(total);
+    out.extend_from_slice(MAGIC);
+    out.extend_from_slice(&VERSION.to_le_bytes());
+    out.extend_from_slice(&[0u8; SALT_LEN]); // salt placeholder
+    out.extend_from_slice(&nonce_bytes);
+    out.extend_from_slice(&buf);
+    Ok(out)
+}
+
+/// Decrypt an envelope produced by [`seal_with_key`] using the same raw key.
+pub fn open_with_key(key: &[u8; KEY_LEN], envelope: &[u8]) -> Result<Vec<u8>, EncryptionError> {
+    let header = 8 + 4 + SALT_LEN + NONCE_LEN;
+    if envelope.len() < header + 16 {
+        return Err(EncryptionError::MalformedEnvelope);
+    }
+    if &envelope[..8] != MAGIC {
+        return Err(EncryptionError::MalformedEnvelope);
+    }
+    let ver = u32::from_le_bytes(envelope[8..12].try_into().unwrap());
+    if ver != VERSION {
+        return Err(EncryptionError::MalformedEnvelope);
+    }
+    let nonce_start = 8 + 4 + SALT_LEN;
+    let nonce_bytes: [u8; NONCE_LEN] =
+        envelope[nonce_start..nonce_start + NONCE_LEN].try_into().unwrap();
+
+    let unbound = UnboundKey::new(&AES_256_GCM, key).expect("valid key length");
+    let mut opening = OpeningKey::new(unbound, FixedNonce(nonce_bytes));
+
+    let mut buf: Vec<u8> = envelope[header..].to_vec();
+    let plaintext = opening
+        .open_in_place(Aad::empty(), &mut buf)
+        .map_err(|_| EncryptionError::AuthenticationFailed)?;
+    Ok(plaintext.to_vec())
+}
+
+// ---------------------------------------------------------------------------
+// Passphrase-based seal / open
+// ---------------------------------------------------------------------------
+
+/// Encrypt `plaintext` using a passphrase.
+///
+/// A random 16-byte PBKDF2 salt is generated, stored in the envelope header,
+/// and used to derive the AES-256 key.
+pub fn seal(passphrase: &[u8], plaintext: &[u8]) -> Result<Vec<u8>, EncryptionError> {
+    let rng = SystemRandom::new();
+
+    let mut salt = [0u8; SALT_LEN];
+    rng.fill(&mut salt).map_err(|_| EncryptionError::RngFailure)?;
+
+    let key = derive_key(passphrase, &salt);
+
+    let mut envelope = seal_with_key(&key, plaintext)?;
+    // Overwrite the zeroed salt placeholder with the real salt.
+    let salt_offset = 8 + 4;
+    envelope[salt_offset..salt_offset + SALT_LEN].copy_from_slice(&salt);
+    Ok(envelope)
+}
+
+/// Decrypt an envelope produced by [`seal`].
+pub fn open(passphrase: &[u8], envelope: &[u8]) -> Result<Vec<u8>, EncryptionError> {
+    let header = 8 + 4 + SALT_LEN + NONCE_LEN;
+    if envelope.len() < header + 16 {
+        return Err(EncryptionError::MalformedEnvelope);
+    }
+    if &envelope[..8] != MAGIC {
+        return Err(EncryptionError::MalformedEnvelope);
+    }
+    let salt_start = 8 + 4;
+    let salt = &envelope[salt_start..salt_start + SALT_LEN];
+    let key = derive_key(passphrase, salt);
+    open_with_key(&key, envelope)
+}
+
+// ---------------------------------------------------------------------------
+// Tests
+// ---------------------------------------------------------------------------
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn seal_open_roundtrip_raw_key() {
+        let key = [0xABu8; 32];
+        let plaintext = b"hello, ClawHDF5 AES-256-GCM!";
+        let envelope = seal_with_key(&key, plaintext).unwrap();
+        let recovered = open_with_key(&key, &envelope).unwrap();
+        assert_eq!(recovered, plaintext);
+    }
+
+    #[test]
+    fn seal_open_roundtrip_passphrase() {
+        let passphrase = b"correct horse battery staple";
+        let plaintext = b"secret agent memory bytes";
+        let envelope = seal(passphrase, plaintext).unwrap();
+        let recovered = open(passphrase, &envelope).unwrap();
+        assert_eq!(recovered, plaintext);
+    }
+
+    #[test]
+    fn wrong_key_fails_authentication() {
+        let key_a = [0x11u8; 32];
+        let key_b = [0x22u8; 32];
+        let envelope = seal_with_key(&key_a, b"sensitive").unwrap();
+        assert!(matches!(open_with_key(&key_b, &envelope), Err(EncryptionError::AuthenticationFailed)));
+    }
+
+    #[test]
+    fn wrong_passphrase_fails_authentication() {
+        let envelope = seal(b"right", b"data").unwrap();
+        assert!(matches!(open(b"wrong", &envelope), Err(EncryptionError::AuthenticationFailed)));
+    }
+
+    #[test]
+    fn tampered_ciphertext_fails_authentication() {
+        let key = [0xCCu8; 32];
+        let mut envelope = seal_with_key(&key, b"data").unwrap();
+        let last = envelope.len() - 1;
+        envelope[last] ^= 0xFF;
+        assert!(matches!(open_with_key(&key, &envelope), Err(EncryptionError::AuthenticationFailed)));
+    }
+
+    #[test]
+    fn malformed_envelope_detected() {
+        assert!(matches!(open_with_key(&[0u8; 32], b"too short"), Err(EncryptionError::MalformedEnvelope)));
+        let mut bad_magic = vec![0u8; 64];
+        assert!(matches!(open_with_key(&[0u8; 32], &bad_magic), Err(EncryptionError::MalformedEnvelope)));
+        // correct magic, wrong version
+        bad_magic[..8].copy_from_slice(MAGIC);
+        bad_magic[8..12].copy_from_slice(&99u32.to_le_bytes());
+        assert!(matches!(open_with_key(&[0u8; 32], &bad_magic), Err(EncryptionError::MalformedEnvelope)));
+    }
+
+    #[test]
+    fn derive_key_is_deterministic() {
+        let k1 = derive_key(b"pass", b"salt1234567890AB");
+        let k2 = derive_key(b"pass", b"salt1234567890AB");
+        assert_eq!(k1, k2);
+    }
+
+    #[test]
+    fn different_salts_produce_different_keys() {
+        let k1 = derive_key(b"pass", b"salt1234567890AB");
+        let k2 = derive_key(b"pass", b"SALT1234567890AB");
+        assert_ne!(k1, k2);
+    }
+
+    #[test]
+    fn empty_plaintext_roundtrip() {
+        let key = [0x77u8; 32];
+        let envelope = seal_with_key(&key, b"").unwrap();
+        let recovered = open_with_key(&key, &envelope).unwrap();
+        assert!(recovered.is_empty());
+    }
+}
@@ -116,14 +116,15 @@ impl GpuSearchBackend {

            // If we don't have an accelerator but now above threshold, try init
            if vectors.len() >= self.threshold
-                && let Ok(mut accel) = clawhdf5_gpu::GpuAccelerator::new() {
-                    let flat: Vec<f32> = vectors.iter().flat_map(|v| v.iter().copied()).collect();
-                    if accel.upload_vectors(&flat, self.dim).is_ok()
-                        && accel.upload_norms(norms).is_ok()
-                    {
-                        self.accelerator = Some(accel);
-                    }
+                && let Ok(mut accel) = clawhdf5_gpu::GpuAccelerator::new()
+            {
+                let flat: Vec<f32> = vectors.iter().flat_map(|v| v.iter().copied()).collect();
+                if accel.upload_vectors(&flat, self.dim).is_ok()
+                    && accel.upload_norms(norms).is_ok()
+                {
+                    self.accelerator = Some(accel);
                }
+            }
        }

        #[cfg(not(feature = "gpu"))]
@@ -439,6 +439,11 @@ impl KnowledgeCache {
        min_activation: f32,
        max_steps: usize,
    ) -> Vec<(u64, f32)> {
+        // decay_factor >= 1.0 means activation never diminishes, so propagation
+        // through cycles accumulates unboundedly for the full max_steps duration.
+        // Clamp to [0.0, 1.0) to guarantee convergence.
+        let decay_factor = decay_factor.clamp(0.0, 1.0 - f32::EPSILON);
+
        let mut activation: HashMap<u64, f32> = HashMap::new();

        // Initialise seeds with activation 1.0.
@@ -1162,4 +1167,63 @@ mod tests {
        assert!(ctx.contains("occupation"));
        assert!(ctx.contains("engineer"));
    }
+
+    // -----------------------------------------------------------------------
+    // Cycle safety — BFS and spreading_activation must not loop infinitely
+    // -----------------------------------------------------------------------
+
+    #[test]
+    fn test_bfs_neighbors_cycle_terminates() {
+        let mut cache = KnowledgeCache::new();
+        let a = cache.add_entity("A", "node", -1);
+        let b = cache.add_entity("B", "node", -1);
+        let c = cache.add_entity("C", "node", -1);
+        // A → B → C → A  (cycle)
+        cache.add_relation(a, b, "link", 1.0);
+        cache.add_relation(b, c, "link", 1.0);
+        cache.add_relation(c, a, "link", 1.0);
+
+        let result = cache.bfs_neighbors(a, 10);
+        // Should visit b and c exactly once, not loop forever.
+        let ids: HashSet<u64> = result.iter().map(|(e, _)| e.id).collect();
+        assert!(ids.contains(&b), "b must be reachable");
+        assert!(ids.contains(&c), "c must be reachable");
+        assert_eq!(result.len(), 2, "only b and c should appear (no duplicates)");
+    }
+
+    #[test]
+    fn test_bfs_neighbors_self_loop_terminates() {
+        let mut cache = KnowledgeCache::new();
+        let a = cache.add_entity("A", "node", -1);
+        // Self-loop: A → A
+        cache.add_relation(a, a, "self", 1.0);
+
+        let result = cache.bfs_neighbors(a, 5);
+        assert!(result.is_empty(), "self-loop seed should not appear in results");
+    }
+
+    #[test]
+    fn test_spreading_activation_cycle_converges() {
+        let mut cache = KnowledgeCache::new();
+        let a = cache.add_entity("A", "node", -1);
+        let b = cache.add_entity("B", "node", -1);
+        let c = cache.add_entity("C", "node", -1);
+        // Cyclic graph A ↔ B ↔ C ↔ A with moderate weights.
+        cache.add_relation(a, b, "link", 0.8);
+        cache.add_relation(b, c, "link", 0.8);
+        cache.add_relation(c, a, "link", 0.8);
+
+        // With decay_factor < 1 the activation decays per step and must
+        // converge within max_steps without panicking or running forever.
+        let result = cache.spreading_activation(&[a], 0.5, 0.001, 20);
+        // At minimum a, b, c should all receive some activation.
+        let activated_ids: HashSet<u64> = result.iter().map(|&(id, _)| id).collect();
+        assert!(activated_ids.contains(&a));
+        assert!(activated_ids.contains(&b));
+        assert!(activated_ids.contains(&c));
+        // Scores must be finite and non-negative.
+        for &(_, score) in &result {
+            assert!(score.is_finite() && score >= 0.0);
+        }
+    }
 }
@@ -20,6 +20,10 @@ pub mod vector_search;

 pub mod agents_md;
 pub mod anomaly;
+#[cfg(feature = "encryption")]
+pub mod encryption;
+#[cfg(feature = "signing")]
+pub mod signing;
 pub mod cache;
 pub mod confidence;
 pub mod consolidation;
@@ -60,6 +64,17 @@ pub fn cosine_similarity_prenorm(
 use std::path::{Path, PathBuf};

 use cache::MemoryCache;
+
+/// Returns the path to the BM25 sidecar file for an HDF5 memory file at `h5_path`.
+///
+/// The sidecar lives next to the `.h5` file with a `.bm25` extension appended
+/// (e.g. `memory.h5` → `memory.h5.bm25`).  It is loaded on `open()` to skip the
+/// O(N × terms) rebuild when the cache is large, and written on every `flush()`.
+fn bm25_sidecar_path(h5_path: &Path) -> PathBuf {
+    let mut p = h5_path.as_os_str().to_owned();
+    p.push(".bm25");
+    PathBuf::from(p)
+}
 #[cfg(feature = "hnsw")]
 use clawhdf5_ann::{DistanceMetric, HnswIndex};
 use ephemeral::{EphemeralConfig, EphemeralStore};
@@ -227,6 +242,10 @@ pub struct HDF5Memory {
    /// search.
    #[cfg(feature = "hnsw")]
    hnsw_synced_len: usize,
+    /// Cached BM25 index. Rebuilt lazily on the first `hybrid_search` call
+    /// after any write; set to `None` on every save / delete / compact to
+    /// ensure it is never stale.
+    bm25_cache: Option<bm25::BM25Index>,
 }

 impl std::fmt::Debug for HDF5Memory {
@@ -266,6 +285,7 @@ impl HDF5Memory {
            hnsw_dirty: false,
            #[cfg(feature = "hnsw")]
            hnsw_synced_len: 0,
+            bm25_cache: None,
        })
    }

@@ -285,6 +305,16 @@ impl HDF5Memory {
            None
        };

+        // Try to load the BM25 sidecar so the first hybrid_search after open()
+        // skips the O(N × terms) rebuild.  Fall back to None (lazy rebuild) if
+        // the sidecar is absent, malformed, or has a mismatched doc count.
+        let bm25_cache = {
+            let sidecar_path = bm25_sidecar_path(&config.path);
+            std::fs::read(&sidecar_path)
+                .ok()
+                .and_then(|b| bm25::BM25Index::from_bytes(&b, cache.chunks.len()))
+        };
+
        Ok(Self {
            config,
            cache,
@@ -301,6 +331,7 @@ impl HDF5Memory {
            hnsw_dirty: true,
            #[cfg(feature = "hnsw")]
            hnsw_synced_len: 0,
+            bm25_cache,
        })
    }

@@ -320,9 +351,35 @@ impl HDF5Memory {
        if let Some(ref mut w) = self.wal {
            w.truncate()?;
        }
+        // Persist the BM25 index alongside the .h5 file so the next open()
+        // can skip the O(N × terms) rebuild.  Only write when we have a cached
+        // index; if there is none, leave any existing sidecar in place.
+        if let Some(ref idx) = self.bm25_cache {
+            let sidecar_path = bm25_sidecar_path(&self.config.path);
+            let bytes = idx.to_bytes();
+            // Best-effort: a sidecar write failure is not fatal — the caller
+            // will rebuild from scratch on the next open().
+            let _ = std::fs::write(&sidecar_path, &bytes);
+        }
        Ok(())
    }

+    /// Path to the `.bm25` sidecar file for this memory store.
+    fn bm25_sidecar_path(&self) -> std::path::PathBuf {
+        bm25_sidecar_path(&self.config.path)
+    }
+
+    /// Try to load the BM25 index from the `.bm25` sidecar file.
+    ///
+    /// Returns `Some(index)` if the sidecar exists and is valid for the current
+    /// cache state (same total chunk count including tombstones).  Returns
+    /// `None` if the sidecar is absent, malformed, or stale.
+    fn load_bm25_sidecar(&self) -> Option<bm25::BM25Index> {
+        let sidecar_path = self.bm25_sidecar_path();
+        let bytes = std::fs::read(&sidecar_path).ok()?;
+        bm25::BM25Index::from_bytes(&bytes, self.cache.chunks.len())
+    }
+
    // ---- HNSW index maintenance --------------------------------------------
    //
    // The index mirrors the cache: HNSW node id == cache index, kept aligned by
@@ -517,6 +574,7 @@ impl HDF5Memory {
            );
            // In-place embedding change: the index node is stale, force rebuild.
            self.hnsw_mark_dirty();
+            self.bm25_cache = None;
            let needs_flush = self
                .wal
                .as_ref()
@@ -558,6 +616,7 @@ impl AgentMemory for HDF5Memory {
            entry.tags,
        );
        self.hnsw_on_insert(idx);
+        self.bm25_cache = None;
        let needs_flush = self
            .wal
            .as_ref()
@@ -586,6 +645,7 @@ impl AgentMemory for HDF5Memory {
        }
        // Batch inserts rebuild the index once rather than node-by-node.
        self.hnsw_mark_dirty();
+        self.bm25_cache = None;
        self.flush()?;
        Ok(indices)
    }
@@ -597,6 +657,7 @@ impl AgentMemory for HDF5Memory {
            )));
        }
        self.hnsw_on_delete(id);
+        self.bm25_cache = None;
        self.flush()?;

        // Auto-compact if threshold exceeded
@@ -614,6 +675,7 @@ impl AgentMemory for HDF5Memory {
        if removed > 0 {
            // Compaction renumbers cache indices; rebuild the index to match.
            self.hnsw_mark_dirty();
+            self.bm25_cache = None;
            self.flush()?;
        }
        Ok(removed)
@@ -1586,7 +1648,7 @@ impl HDF5Memory {
        k: usize,
    ) -> Vec<SearchResult> {
        // Persistent tier.
-        let persistent = self.hybrid_search(query_embedding, query_text, 0.7, 0.3, k);
+        let persistent = self.hybrid_search(query_embedding, query_text, 0.4, 0.6, k);
        const EPHEMERAL_BOOST: f32 = 1.2;
        let mut results = persistent;

@@ -133,8 +133,63 @@ impl MediaRef {
            checksum: Some(cs),
        }
    }
+
+    /// Validate this reference against a sandbox directory and a URL scheme allowlist.
+    ///
+    /// * `Path` references are canonicalized and checked to be within `sandbox`
+    ///   (if `sandbox` is `Some`).  A path that escapes the sandbox via `..`
+    ///   or symlinks is rejected with an error.
+    /// * `Url` references must begin with one of the schemes in
+    ///   [`ALLOWED_URL_SCHEMES`].  An empty or scheme-less URL is rejected.
+    /// * `Inline` references are always valid (no external resolution).
+    ///
+    /// Returns `Ok(())` when the reference passes all checks, or an `Err`
+    /// with a human-readable reason otherwise.
+    pub fn validate(&self, sandbox: Option<&std::path::Path>) -> Result<(), String> {
+        match &self.ref_type {
+            MediaRefType::Path(raw) => {
+                let candidate = std::path::Path::new(raw);
+                let canonical = candidate
+                    .canonicalize()
+                    .map_err(|e| format!("path canonicalization failed for {raw:?}: {e}"))?;
+                if let Some(root) = sandbox {
+                    let root_canonical = root
+                        .canonicalize()
+                        .map_err(|e| format!("sandbox canonicalization failed: {e}"))?;
+                    if !canonical.starts_with(&root_canonical) {
+                        return Err(format!(
+                            "path {canonical:?} escapes sandbox {root_canonical:?}"
+                        ));
+                    }
+                }
+                Ok(())
+            }
+            MediaRefType::Url(url) => {
+                let scheme_end = url
+                    .find("://")
+                    .ok_or_else(|| format!("URL {url:?} has no scheme"))?;
+                let scheme = &url[..scheme_end];
+                if ALLOWED_URL_SCHEMES.contains(&scheme) {
+                    Ok(())
+                } else {
+                    Err(format!(
+                        "URL scheme {scheme:?} is not in the allowlist {:?}",
+                        ALLOWED_URL_SCHEMES
+                    ))
+                }
+            }
+            MediaRefType::Inline(_) => Ok(()),
+        }
+    }
 }

+/// URL schemes that are permitted in `MediaRef::Url` references.
+///
+/// Any scheme not in this list is rejected by [`MediaRef::validate`].  Keeping
+/// the list explicit prevents `file://` or `data:` URIs from being smuggled in
+/// via adversarial memory content.
+pub const ALLOWED_URL_SCHEMES: &[&str] = &["https", "http"];
+
 // ---------------------------------------------------------------------------
 // FNV-1a helper (no external deps)
 // ---------------------------------------------------------------------------
@@ -807,4 +862,69 @@ mod tests {
        let r = store.get_record(id).unwrap();
        assert_eq!(r.metadata.get("source").unwrap(), "camera-1");
    }
+
+    // -----------------------------------------------------------------------
+    // MediaRef::validate — sandboxing
+    // -----------------------------------------------------------------------
+
+    #[test]
+    fn inline_always_valid() {
+        let r = MediaRef::inline(vec![1, 2, 3], "application/octet-stream");
+        assert!(r.validate(None).is_ok());
+    }
+
+    #[test]
+    fn url_allowed_scheme_https() {
+        let r = MediaRef::url("https://example.com/img.png", "image/png");
+        assert!(r.validate(None).is_ok());
+    }
+
+    #[test]
+    fn url_allowed_scheme_http() {
+        let r = MediaRef::url("http://example.com/img.png", "image/png");
+        assert!(r.validate(None).is_ok());
+    }
+
+    #[test]
+    fn url_disallowed_scheme_file() {
+        let r = MediaRef::url("file:///etc/passwd", "text/plain");
+        assert!(r.validate(None).is_err());
+    }
+
+    #[test]
+    fn url_disallowed_scheme_data() {
+        let r = MediaRef::url("data:text/html,<script>", "text/html");
+        assert!(r.validate(None).is_err());
+    }
+
+    #[test]
+    fn url_no_scheme_rejected() {
+        let r = MediaRef::url("not-a-url", "text/plain");
+        assert!(r.validate(None).is_err());
+    }
+
+    #[test]
+    fn path_within_sandbox_accepted() {
+        let dir = tempfile::tempdir().unwrap();
+        let file = dir.path().join("audio.mp3");
+        std::fs::write(&file, b"dummy").unwrap();
+        let r = MediaRef::path(file.to_str().unwrap(), "audio/mpeg");
+        assert!(r.validate(Some(dir.path())).is_ok());
+    }
+
+    #[test]
+    fn path_outside_sandbox_rejected() {
+        let sandbox = tempfile::tempdir().unwrap();
+        // /tmp itself exists and is outside the sandbox subdir
+        let r = MediaRef::path("/tmp", "inode/directory");
+        let result = r.validate(Some(sandbox.path()));
+        // May fail at canonicalization or at the starts_with check; either is correct
+        assert!(result.is_err());
+    }
+
+    #[test]
+    fn path_nonexistent_rejected_at_canonicalize() {
+        let r = MediaRef::path("/this/path/does/not/exist/abc123", "text/plain");
+        assert!(r.validate(None).is_err());
+    }
 }
@@ -535,7 +535,7 @@ impl MemoryBackend for ClawhdfBackend {
        let candidates = k.saturating_mul(3).max(10);
        let raw = self
            .memory
-            .hybrid_search(query_embedding, query_text, 0.7, 0.3, candidates);
+            .hybrid_search(query_embedding, query_text, 0.4, 0.6, candidates);

        if raw.is_empty() {
            return Vec::new();
@@ -1,7 +1,9 @@
 //! Memory provenance tracking and integrity verification.
 //!
-//! Records the origin, authorship, and integrity of every memory chunk
-//! so the system can detect tampering and trace data lineage.
+//! Records the origin, authorship, and a content hash of every memory chunk
+//! so the system can detect *accidental* corruption and trace data lineage.
+//! The hash is unkeyed (see [`fnv1a_64`]) — this is not a tamper-evidence or
+//! authenticity guarantee.

 use std::collections::HashMap;

@@ -11,6 +13,10 @@ pub use crate::consolidation::MemorySource;
 // Hash helper (std-only FNV-1a 64-bit)
 // ---------------------------------------------------------------------------

+/// Unkeyed, non-cryptographic FNV-1a hash for detecting accidental content
+/// corruption. It is trivially forgeable by anyone able to modify the stored
+/// data, since they can recompute and overwrite the stored hash alongside
+/// it — do not rely on this as a tamper-evidence or authenticity control.
 fn fnv1a_64(text: &str) -> u64 {
    const OFFSET: u64 = 14_695_981_039_346_656_037;
    const PRIME: u64 = 1_099_511_628_211;
@@ -114,6 +120,11 @@ impl ProvenanceStore {

    /// Re-hash `current_chunk` and compare against the stored hash.
    /// Returns `true` if the content matches (integrity intact).
+    ///
+    /// This only detects accidental corruption: the hash is unkeyed, so an
+    /// actor able to modify the stored chunk can also recompute and
+    /// overwrite the stored hash. Do not treat a `true` result as proof the
+    /// data hasn't been tampered with.
    pub fn verify_integrity(&self, record_id: u64, current_chunk: &str) -> bool {
        match self.records.get(&record_id) {
            Some(p) => p.content_hash == fnv1a_64(current_chunk),
@@ -26,9 +26,7 @@ impl HDF5Memory {
    ) -> Vec<(usize, f32)> {
        self.ensure_hnsw_fresh();
        match self.hnsw.as_ref() {
-            Some(index)
-                if !index.is_empty() && index.dimension() == query_embedding.len() =>
-            {
+            Some(index) if !index.is_empty() && index.dimension() == query_embedding.len() => {
                // Over-fetch so the merge sees a useful vector pool; cosine
                // distance from the index converts back to similarity (1 - d).
                let pool = (k * 8).max(64);
@@ -38,7 +36,13 @@ impl HDF5Memory {
                    .map(|(id, dist)| (id, 1.0 - dist))
                    .collect();
                let kw_scores = bm25.search(query_text, self.cache.len());
-                hybrid::merge_vector_keyword(vec_scores, kw_scores, vector_weight, keyword_weight, k)
+                hybrid::merge_vector_keyword(
+                    vec_scores,
+                    kw_scores,
+                    vector_weight,
+                    keyword_weight,
+                    k,
+                )
            }
            _ => hybrid::hybrid_search(
                query_embedding,
@@ -86,7 +90,16 @@ impl HDF5Memory {
        keyword_weight: f32,
        k: usize,
    ) -> Vec<SearchResult> {
-        let bm25 = bm25::BM25Index::build(&self.cache.chunks, &self.cache.tombstones);
+        // Lazily build the BM25 index once and reuse across searches.  The
+        // cache is invalidated (set to None) by every save / delete / compact
+        // call so it is never stale.  We take() the index out of the Option
+        // so that we can pass &bm25 while also holding &mut self for the
+        // vector search path; it is put back immediately after.
+        if self.bm25_cache.is_none() {
+            self.bm25_cache =
+                Some(bm25::BM25Index::build(&self.cache.chunks, &self.cache.tombstones));
+        }
+        let bm25 = self.bm25_cache.take().expect("just built");
        let scored = self.vector_keyword_search(
            query_embedding,
            query_text,
@@ -117,6 +130,9 @@ impl HDF5Memory {

        let hit_indices: Vec<usize> = results.iter().map(|r| r.index).collect();
        self.apply_hebbian_boost(&hit_indices);
+        // Restore the BM25 index before flush so it survives the write.
+        // flush() does not invalidate bm25_cache; only mutating writes do.
+        self.bm25_cache = Some(bm25);
        self.flush().ok();

        results
@@ -0,0 +1,284 @@
+//! Ed25519 file signing for ClawBrainHub `.brain` files.
+//!
+//! # Sidecar format
+//!
+//! ```text
+//! [8 bytes magic "CLAWSIG\x00"]
+//! [4 bytes version = 1, little-endian u32]
+//! [1 byte public-key length = 32]
+//! [32 bytes Ed25519 public key (raw)]
+//! [1 byte signature length = 64]
+//! [64 bytes Ed25519 signature over the file's SHA-512 digest]
+//! ```
+//!
+//! The signature covers the **SHA-512 hash** of the file content rather than
+//! the raw bytes so that large files do not need to be fully loaded into memory
+//! during verification.  Ring's Ed25519 implementation hashes internally, so
+//! we pass the entire content and let ring handle it.
+
+use std::io::Read;
+use std::path::Path;
+
+use ring::rand::SystemRandom;
+use ring::signature::{self, Ed25519KeyPair, KeyPair};
+
+/// Sidecar file magic.
+const MAGIC: &[u8; 8] = b"CLAWSIG\x00";
+/// Sidecar format version.
+const VERSION: u32 = 1;
+
+#[derive(Debug)]
+pub enum SigningError {
+    /// Sidecar is too short, has wrong magic, or unsupported version.
+    MalformedSidecar,
+    /// Ed25519 signature did not verify against the file content.
+    InvalidSignature,
+    /// Key generation or signing operation failed.
+    KeyError(String),
+    /// I/O error reading/writing a file.
+    Io(std::io::Error),
+}
+
+impl std::fmt::Display for SigningError {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        match self {
+            SigningError::MalformedSidecar => write!(f, "malformed signing sidecar"),
+            SigningError::InvalidSignature => write!(f, "Ed25519 signature verification failed"),
+            SigningError::KeyError(e) => write!(f, "key error: {e}"),
+            SigningError::Io(e) => write!(f, "I/O error: {e}"),
+        }
+    }
+}
+
+impl From<std::io::Error> for SigningError {
+    fn from(e: std::io::Error) -> Self {
+        SigningError::Io(e)
+    }
+}
+
+// ---------------------------------------------------------------------------
+// Key generation
+// ---------------------------------------------------------------------------
+
+/// Generate a new Ed25519 key pair.
+///
+/// Returns `(pkcs8_document, public_key_bytes)`.  The PKCS#8 document should
+/// be stored securely (it contains the private key).  The public key is needed
+/// for verification and can be distributed freely.
+pub fn generate_keypair() -> Result<(Vec<u8>, Vec<u8>), SigningError> {
+    let rng = SystemRandom::new();
+    let pkcs8 = Ed25519KeyPair::generate_pkcs8(&rng)
+        .map_err(|_| SigningError::KeyError("key generation failed".into()))?;
+    let pair = Ed25519KeyPair::from_pkcs8(pkcs8.as_ref())
+        .map_err(|_| SigningError::KeyError("pkcs8 decode failed".into()))?;
+    let pubkey = pair.public_key().as_ref().to_vec();
+    Ok((pkcs8.as_ref().to_vec(), pubkey))
+}
+
+// ---------------------------------------------------------------------------
+// Sign / verify (in-memory)
+// ---------------------------------------------------------------------------
+
+/// Sign `data` with a PKCS#8-encoded Ed25519 private key.
+///
+/// Returns the raw 64-byte Ed25519 signature.
+pub fn sign(pkcs8_key: &[u8], data: &[u8]) -> Result<Vec<u8>, SigningError> {
+    let pair = Ed25519KeyPair::from_pkcs8(pkcs8_key)
+        .map_err(|_| SigningError::KeyError("invalid PKCS#8 key".into()))?;
+    Ok(pair.sign(data).as_ref().to_vec())
+}
+
+/// Verify that `signature` is a valid Ed25519 signature of `data` under
+/// `public_key` (raw 32-byte key).
+///
+/// Returns `true` when the signature is valid.
+pub fn verify(public_key: &[u8], data: &[u8], signature: &[u8]) -> bool {
+    let peer = signature::UnparsedPublicKey::new(&signature::ED25519, public_key);
+    peer.verify(data, signature).is_ok()
+}
+
+// ---------------------------------------------------------------------------
+// Sidecar helpers
+// ---------------------------------------------------------------------------
+
+/// Serialize a public key and signature into a sidecar envelope.
+pub fn encode_sidecar(public_key: &[u8], sig: &[u8]) -> Vec<u8> {
+    let mut out = Vec::with_capacity(8 + 4 + 1 + public_key.len() + 1 + sig.len());
+    out.extend_from_slice(MAGIC);
+    out.extend_from_slice(&VERSION.to_le_bytes());
+    out.push(public_key.len() as u8);
+    out.extend_from_slice(public_key);
+    out.push(sig.len() as u8);
+    out.extend_from_slice(sig);
+    out
+}
+
+/// Parse a sidecar envelope, returning `(public_key, signature)`.
+pub fn decode_sidecar(sidecar: &[u8]) -> Result<(Vec<u8>, Vec<u8>), SigningError> {
+    if sidecar.len() < 8 + 4 + 1 + 1 {
+        return Err(SigningError::MalformedSidecar);
+    }
+    if &sidecar[..8] != MAGIC {
+        return Err(SigningError::MalformedSidecar);
+    }
+    let ver = u32::from_le_bytes(sidecar[8..12].try_into().unwrap());
+    if ver != VERSION {
+        return Err(SigningError::MalformedSidecar);
+    }
+    let mut pos = 12usize;
+    let pk_len = sidecar[pos] as usize;
+    pos += 1;
+    if pos + pk_len + 1 > sidecar.len() {
+        return Err(SigningError::MalformedSidecar);
+    }
+    let public_key = sidecar[pos..pos + pk_len].to_vec();
+    pos += pk_len;
+    let sig_len = sidecar[pos] as usize;
+    pos += 1;
+    if pos + sig_len > sidecar.len() {
+        return Err(SigningError::MalformedSidecar);
+    }
+    let signature = sidecar[pos..pos + sig_len].to_vec();
+    Ok((public_key, signature))
+}
+
+// ---------------------------------------------------------------------------
+// File-level helpers
+// ---------------------------------------------------------------------------
+
+/// Returns the path for the sidecar signature file next to `file_path`.
+///
+/// Example: `memory.brain` → `memory.brain.sig`
+pub fn sidecar_path(file_path: &Path) -> std::path::PathBuf {
+    let mut s = file_path.as_os_str().to_owned();
+    s.push(".sig");
+    std::path::PathBuf::from(s)
+}
+
+/// Sign `file_path` with `pkcs8_key` and write the sidecar (`.sig` file).
+pub fn sign_file(file_path: &Path, pkcs8_key: &[u8]) -> Result<(), SigningError> {
+    let data = read_file(file_path)?;
+    let pair = Ed25519KeyPair::from_pkcs8(pkcs8_key)
+        .map_err(|_| SigningError::KeyError("invalid PKCS#8 key".into()))?;
+    let pubkey = pair.public_key().as_ref().to_vec();
+    let sig = pair.sign(&data).as_ref().to_vec();
+    let sidecar = encode_sidecar(&pubkey, &sig);
+    let sidecar_p = sidecar_path(file_path);
+    std::fs::write(&sidecar_p, &sidecar)?;
+    Ok(())
+}
+
+/// Verify the signature sidecar for `file_path`.
+///
+/// Reads the `.sig` sidecar next to the file, parses it, and checks the
+/// signature against `file_path`'s current contents.
+///
+/// Returns `Ok(true)` if the signature is valid, `Ok(false)` if the sidecar
+/// does not exist (not yet signed), and `Err(_)` on parse or I/O failures.
+pub fn verify_file(file_path: &Path) -> Result<bool, SigningError> {
+    let sidecar_p = sidecar_path(file_path);
+    if !sidecar_p.exists() {
+        return Ok(false);
+    }
+    let sidecar_bytes = read_file(&sidecar_p)?;
+    let (public_key, sig) = decode_sidecar(&sidecar_bytes)?;
+    let data = read_file(file_path)?;
+    if verify(&public_key, &data, &sig) {
+        Ok(true)
+    } else {
+        Err(SigningError::InvalidSignature)
+    }
+}
+
+fn read_file(path: &Path) -> Result<Vec<u8>, SigningError> {
+    let mut f = std::fs::File::open(path)?;
+    let mut buf = Vec::new();
+    f.read_to_end(&mut buf)?;
+    Ok(buf)
+}
+
+// ---------------------------------------------------------------------------
+// Tests
+// ---------------------------------------------------------------------------
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use std::io::Write;
+    use tempfile::NamedTempFile;
+
+    #[test]
+    fn generate_and_sign_verify() {
+        let (pkcs8, pubkey) = generate_keypair().unwrap();
+        let data = b"ClawBrainHub .brain file content";
+        let sig = sign(&pkcs8, data).unwrap();
+        assert_eq!(sig.len(), 64);
+        assert!(verify(&pubkey, data, &sig));
+    }
+
+    #[test]
+    fn wrong_public_key_fails() {
+        let (pkcs8, _) = generate_keypair().unwrap();
+        let (_, other_pubkey) = generate_keypair().unwrap();
+        let sig = sign(&pkcs8, b"data").unwrap();
+        assert!(!verify(&other_pubkey, b"data", &sig));
+    }
+
+    #[test]
+    fn tampered_data_fails() {
+        let (pkcs8, pubkey) = generate_keypair().unwrap();
+        let sig = sign(&pkcs8, b"original").unwrap();
+        assert!(!verify(&pubkey, b"tampered", &sig));
+    }
+
+    #[test]
+    fn sidecar_encode_decode_roundtrip() {
+        let pubkey = vec![0xAAu8; 32];
+        let sig = vec![0xBBu8; 64];
+        let sidecar = encode_sidecar(&pubkey, &sig);
+        let (pk2, sig2) = decode_sidecar(&sidecar).unwrap();
+        assert_eq!(pk2, pubkey);
+        assert_eq!(sig2, sig);
+    }
+
+    #[test]
+    fn malformed_sidecar_detected() {
+        assert!(matches!(decode_sidecar(b"short"), Err(SigningError::MalformedSidecar)));
+        let mut bad = vec![0u8; 20];
+        assert!(matches!(decode_sidecar(&bad), Err(SigningError::MalformedSidecar)));
+        bad[..8].copy_from_slice(MAGIC);
+        bad[8..12].copy_from_slice(&99u32.to_le_bytes()); // wrong version
+        assert!(matches!(decode_sidecar(&bad), Err(SigningError::MalformedSidecar)));
+    }
+
+    #[test]
+    fn sign_and_verify_file() {
+        let (pkcs8, _) = generate_keypair().unwrap();
+        let mut f = NamedTempFile::new().unwrap();
+        f.write_all(b"brain file content").unwrap();
+        f.flush().unwrap();
+        sign_file(f.path(), &pkcs8).unwrap();
+        // sidecar should exist
+        assert!(sidecar_path(f.path()).exists());
+        // verification should succeed
+        assert!(matches!(verify_file(f.path()), Ok(true)));
+    }
+
+    #[test]
+    fn verify_file_no_sidecar_returns_false() {
+        let f = NamedTempFile::new().unwrap();
+        assert!(matches!(verify_file(f.path()), Ok(false)));
+    }
+
+    #[test]
+    fn verify_file_detects_modified_content() {
+        let (pkcs8, _) = generate_keypair().unwrap();
+        let mut f = NamedTempFile::new().unwrap();
+        f.write_all(b"original content").unwrap();
+        f.flush().unwrap();
+        sign_file(f.path(), &pkcs8).unwrap();
+        // Overwrite the file with different content
+        std::fs::write(f.path(), b"tampered content").unwrap();
+        assert!(matches!(verify_file(f.path()), Err(SigningError::InvalidSignature)));
+    }
+}
@@ -7,10 +7,29 @@ use std::fs::{File, OpenOptions};
 use std::io::{Read, Seek, SeekFrom, Write};
 use std::path::{Path, PathBuf};

+use clawhdf5_format::checksum::crc32;
+
 use crate::MemoryError;

 const WAL_MAGIC: [u8; 4] = [0x45, 0x48, 0x57, 0x4C]; // "EHWL"
-const WAL_VERSION: u8 = 1;
+
+/// Current WAL format version: every entry ends with a 4-byte CRC32 trailer
+/// (see [`TeeReader`]) so a bit-flip is detected and replay stops there
+/// instead of silently accepting corrupted data.
+const WAL_VERSION: u8 = 2;
+
+/// The only other WAL version this crate still knows how to *read*: no
+/// per-entry CRC trailer. Written by versions of this crate before the CRC32
+/// hardening. `WalFile::open` migrates a legacy file to [`WAL_VERSION`] by
+/// recreating it fresh — safe because every real call site reads existing
+/// entries via [`WalFile::read_entries`] before calling `open` (see
+/// `HDF5Memory::open`), so no data is lost.
+const WAL_VERSION_LEGACY_NO_CRC: u8 = 1;
+
+/// Upper bound on a single length-prefixed WAL field (string bytes, or
+/// embedding element count), to reject a corrupted/truncated WAL length
+/// claim before allocating a large buffer for it.
+const MAX_WAL_FIELD_LEN: usize = 64 * 1024 * 1024;

 #[repr(u8)]
 #[derive(Debug, Clone, Copy, PartialEq, Eq)]
@@ -62,6 +81,11 @@ pub struct WalFile {

 impl WalFile {
    /// Open or create a WAL file. If it exists, read the header and entry count.
+    ///
+    /// A legacy (pre-CRC) WAL file is migrated to the current format by
+    /// recreating it fresh — see [`WAL_VERSION_LEGACY_NO_CRC`]. Callers that
+    /// need the legacy file's entries must call [`WalFile::read_entries`]
+    /// first, before calling `open`.
    pub fn open(path: &Path) -> Result<Self, MemoryError> {
        if path.exists() {
            // Read existing header
@@ -77,30 +101,34 @@ impl WalFile {
            }
            let mut ver = [0u8; 1];
            f.read_exact(&mut ver)?;
-            if ver[0] != WAL_VERSION {
-                return Err(MemoryError::Schema(format!(
-                    "unsupported WAL version {}",
-                    ver[0]
-                )));
+            match ver[0] {
+                WAL_VERSION => {
+                    let mut count_buf = [0u8; 4];
+                    f.read_exact(&mut count_buf)?;
+                    let entry_count = u32::from_le_bytes(count_buf);
+                    // Seek to end for appending
+                    f.seek(SeekFrom::End(0))?;
+                    Ok(Self {
+                        path: path.to_path_buf(),
+                        file: Some(f),
+                        entry_count,
+                        pending_header_sync: 0,
+                    })
+                }
+                WAL_VERSION_LEGACY_NO_CRC => {
+                    drop(f);
+                    let f = create_fresh_wal_file(path)?;
+                    Ok(Self {
+                        path: path.to_path_buf(),
+                        file: Some(f),
+                        entry_count: 0,
+                        pending_header_sync: 0,
+                    })
+                }
+                v => Err(MemoryError::Schema(format!("unsupported WAL version {v}"))),
            }
-            let mut count_buf = [0u8; 4];
-            f.read_exact(&mut count_buf)?;
-            let entry_count = u32::from_le_bytes(count_buf);
-            // Seek to end for appending
-            f.seek(SeekFrom::End(0))?;
-            Ok(Self {
-                path: path.to_path_buf(),
-                file: Some(f),
-                entry_count,
-                pending_header_sync: 0,
-            })
        } else {
-            // Create new WAL
-            let mut f = File::create(path)?;
-            f.write_all(&WAL_MAGIC)?;
-            f.write_all(&[WAL_VERSION])?;
-            f.write_all(&0u32.to_le_bytes())?;
-            f.flush()?;
+            let f = create_fresh_wal_file(path)?;
            Ok(Self {
                path: path.to_path_buf(),
                file: Some(f),
@@ -140,6 +168,9 @@ impl WalFile {
        serialize_str(&mut buf, &entry.session_id);
        serialize_str(&mut buf, &entry.tags);

+        let crc = crc32(&buf);
+        buf.extend_from_slice(&crc.to_le_bytes());
+
        let f = self
            .file
            .as_mut()
@@ -156,10 +187,12 @@ impl WalFile {

    /// Append a tombstone entry (deletion).
    pub fn append_tombstone(&mut self, index: usize, timestamp: f64) -> Result<(), MemoryError> {
-        let mut buf = [0u8; 1 + 8 + 4]; // type + timestamp + index
+        let mut buf = [0u8; 1 + 8 + 4 + 4]; // type + timestamp + index + crc32
        buf[0] = WalEntryType::Tombstone as u8;
        buf[1..9].copy_from_slice(&timestamp.to_le_bytes());
        buf[9..13].copy_from_slice(&(index as u32).to_le_bytes());
+        let crc = crc32(&buf[..13]);
+        buf[13..17].copy_from_slice(&crc.to_le_bytes());

        let f = self
            .file
@@ -180,7 +213,9 @@ impl WalFile {
    /// Reads until EOF — the header `entry_count` is used only for pre-allocation
    /// (and may be stale if written with deferred group-commit updates). This
    /// tolerates both truncated files (crash mid-write) and stale header counts
-    /// (crash before the next group-commit header sync).
+    /// (crash before the next group-commit header sync). On a `WAL_VERSION`
+    /// file, a CRC32 mismatch on an entry is treated the same way — replay
+    /// stops there rather than accepting corrupted data.
    pub fn read_entries(path: &Path) -> Result<Vec<WalEntry>, MemoryError> {
        if !path.exists() {
            return Ok(Vec::new());
@@ -192,81 +227,45 @@ impl WalFile {
        if header[0..4] != WAL_MAGIC {
            return Err(MemoryError::Schema("invalid WAL magic bytes".into()));
        }
-        if header[4] != WAL_VERSION {
-            return Err(MemoryError::Schema(format!(
-                "unsupported WAL version {}",
-                header[4]
-            )));
-        }
        // entry_count is a pre-allocation hint only — we read until EOF.
        let entry_count_hint = u32::from_le_bytes([header[5], header[6], header[7], header[8]]);
        let mut entries = Vec::with_capacity(entry_count_hint as usize);

-        loop {
-            // Read entry type — EOF here is normal end-of-log, not an error
-            let mut type_buf = [0u8; 1];
-            if f.read_exact(&mut type_buf).is_err() {
-                break;
-            }
-            let entry_type = match WalEntryType::from_u8(type_buf[0]) {
-                Some(et) => et,
-                None => break,
-            };
-
-            let mut ts_buf = [0u8; 8];
-            if f.read_exact(&mut ts_buf).is_err() {
-                break;
-            }
-            let timestamp = f64::from_le_bytes(ts_buf);
-
-            match entry_type {
-                WalEntryType::Save => {
-                    let Ok(chunk) = read_len_prefixed_str(&mut f) else {
-                        break;
-                    };
-                    let Ok(embedding) = read_embedding(&mut f) else {
-                        break;
-                    };
-                    let Ok(source_channel) = read_len_prefixed_str(&mut f) else {
-                        break;
-                    };
-                    let Ok(session_id) = read_len_prefixed_str(&mut f) else {
-                        break;
-                    };
-                    let Ok(tags) = read_len_prefixed_str(&mut f) else {
-                        break;
-                    };
-                    entries.push(WalEntry {
-                        entry_type,
-                        timestamp,
-                        chunk,
-                        embedding,
-                        source_channel,
-                        session_id,
-                        tags,
-                        tombstone_index: None,
-                    });
+        match header[4] {
+            WAL_VERSION => loop {
+                let raw_and_result = {
+                    let mut tee = TeeReader::new(&mut f);
+                    let result = read_one_entry(&mut tee);
+                    (tee.into_buf(), result)
+                };
+                let (raw, result) = raw_and_result;
+                let entry_opt = match result {
+                    Err(()) => break,
+                    Ok(v) => v,
+                };
+                let mut crc_buf = [0u8; 4];
+                if f.read_exact(&mut crc_buf).is_err() {
+                    break;
                }
-                WalEntryType::Tombstone => {
-                    let mut idx_buf = [0u8; 4];
-                    if f.read_exact(&mut idx_buf).is_err() {
-                        break;
-                    }
-                    let idx = u32::from_le_bytes(idx_buf) as usize;
-                    entries.push(WalEntry {
-                        entry_type,
-                        timestamp,
-                        chunk: String::new(),
-                        embedding: Vec::new(),
-                        source_channel: String::new(),
-                        session_id: String::new(),
-                        tags: String::new(),
-                        tombstone_index: Some(idx),
-                    });
+                let stored_crc = u32::from_le_bytes(crc_buf);
+                if crc32(&raw) != stored_crc {
+                    // Corruption detected — stop replay here, same as a clean
+                    // truncation/EOF, rather than accepting the bad entry.
+                    break;
                }
-                WalEntryType::ActivationUpdate => {
-                    // Reserved for future use
+                if let Some(entry) = entry_opt {
+                    entries.push(entry);
                }
+            },
+            WAL_VERSION_LEGACY_NO_CRC => loop {
+                match read_one_entry(&mut f) {
+                    Err(()) => break,
+                    Ok(Some(entry)) => entries.push(entry),
+                    Ok(None) => {}
+                }
+            },
+            v => {
+                return Err(MemoryError::Schema(format!("unsupported WAL version {v}")));
            }
        }
        Ok(entries)
@@ -276,11 +275,7 @@ impl WalFile {
    pub fn truncate(&mut self) -> Result<(), MemoryError> {
        // Close existing handle and recreate
        self.file = None;
-        let mut f = File::create(&self.path)?;
-        f.write_all(&WAL_MAGIC)?;
-        f.write_all(&[WAL_VERSION])?;
-        f.write_all(&0u32.to_le_bytes())?;
-        f.flush()?;
+        let f = create_fresh_wal_file(&self.path)?;
        self.file = Some(f);
        self.entry_count = 0;
        self.pending_header_sync = 0;
@@ -345,19 +340,30 @@ fn serialize_str(buf: &mut Vec<u8>, s: &str) {
    buf.extend_from_slice(bytes);
 }

-fn read_len_prefixed_str(f: &mut File) -> Result<String, MemoryError> {
+fn read_len_prefixed_str<R: Read>(f: &mut R) -> Result<String, MemoryError> {
    let mut len_buf = [0u8; 4];
    f.read_exact(&mut len_buf)?;
    let len = u32::from_le_bytes(len_buf) as usize;
+    if len > MAX_WAL_FIELD_LEN {
+        return Err(MemoryError::Schema(format!(
+            "WAL string field length {len} exceeds max {MAX_WAL_FIELD_LEN}"
+        )));
+    }
    let mut buf = vec![0u8; len];
    f.read_exact(&mut buf)?;
    String::from_utf8(buf).map_err(|e| MemoryError::Schema(format!("invalid UTF-8 in WAL: {e}")))
 }

-fn read_embedding(f: &mut File) -> Result<Vec<f32>, MemoryError> {
+fn read_embedding<R: Read>(f: &mut R) -> Result<Vec<f32>, MemoryError> {
    let mut len_buf = [0u8; 4];
    f.read_exact(&mut len_buf)?;
    let count = u32::from_le_bytes(len_buf) as usize;
+    if count > MAX_WAL_FIELD_LEN / 4 {
+        return Err(MemoryError::Schema(format!(
+            "WAL embedding element count {count} exceeds max {}",
+            MAX_WAL_FIELD_LEN / 4
+        )));
+    }
    let mut vals = Vec::with_capacity(count);
    for _ in 0..count {
        let mut val_buf = [0u8; 4];
@@ -367,6 +373,99 @@ fn read_embedding(f: &mut File) -> Result<Vec<f32>, MemoryError> {
    Ok(vals)
 }

+/// Create a fresh WAL file at `path` with the current-version header,
+/// truncating/overwriting anything already there.
+fn create_fresh_wal_file(path: &Path) -> Result<File, MemoryError> {
+    let mut f = File::create(path)?;
+    f.write_all(&WAL_MAGIC)?;
+    f.write_all(&[WAL_VERSION])?;
+    f.write_all(&0u32.to_le_bytes())?;
+    f.flush()?;
+    Ok(f)
+}
+
+/// Wraps a [`Read`]er, accumulating every byte actually consumed (including
+/// via `read_exact`, which is implemented in terms of `read`) into an
+/// internal buffer — used to capture a WAL entry's raw bytes for CRC32
+/// verification without needing to know its length up front.
+struct TeeReader<'a, R: Read> {
+    inner: &'a mut R,
+    buf: Vec<u8>,
+}
+
+impl<'a, R: Read> TeeReader<'a, R> {
+    fn new(inner: &'a mut R) -> Self {
+        Self {
+            inner,
+            buf: Vec::new(),
+        }
+    }
+
+    fn into_buf(self) -> Vec<u8> {
+        self.buf
+    }
+}
+
+impl<R: Read> Read for TeeReader<'_, R> {
+    fn read(&mut self, out: &mut [u8]) -> std::io::Result<usize> {
+        let n = self.inner.read(out)?;
+        self.buf.extend_from_slice(&out[..n]);
+        Ok(n)
+    }
+}
+
+/// Read one WAL entry (type + timestamp + type-specific payload) from `r`.
+///
+/// Returns `Ok(None)` for entry types with no representable `WalEntry` (only
+/// `ActivationUpdate`, reserved for future use). Returns `Err(())` on any
+/// read failure or unrecognized entry type — the caller treats this the same
+/// as a clean end-of-log (crash-mid-write tolerance).
+fn read_one_entry<R: Read>(r: &mut R) -> Result<Option<WalEntry>, ()> {
+    let mut type_buf = [0u8; 1];
+    r.read_exact(&mut type_buf).map_err(|_| ())?;
+    let entry_type = WalEntryType::from_u8(type_buf[0]).ok_or(())?;
+
+    let mut ts_buf = [0u8; 8];
+    r.read_exact(&mut ts_buf).map_err(|_| ())?;
+    let timestamp = f64::from_le_bytes(ts_buf);
+
+    match entry_type {
+        WalEntryType::Save => {
+            let chunk = read_len_prefixed_str(r).map_err(|_| ())?;
+            let embedding = read_embedding(r).map_err(|_| ())?;
+            let source_channel = read_len_prefixed_str(r).map_err(|_| ())?;
+            let session_id = read_len_prefixed_str(r).map_err(|_| ())?;
+            let tags = read_len_prefixed_str(r).map_err(|_| ())?;
+            Ok(Some(WalEntry {
+                entry_type,
+                timestamp,
+                chunk,
+                embedding,
+                source_channel,
+                session_id,
+                tags,
+                tombstone_index: None,
+            }))
+        }
+        WalEntryType::Tombstone => {
+            let mut idx_buf = [0u8; 4];
+            r.read_exact(&mut idx_buf).map_err(|_| ())?;
+            let idx = u32::from_le_bytes(idx_buf) as usize;
+            Ok(Some(WalEntry {
+                entry_type,
+                timestamp,
+                chunk: String::new(),
+                embedding: Vec::new(),
+                source_channel: String::new(),
+                session_id: String::new(),
+                tags: String::new(),
+                tombstone_index: Some(idx),
+            }))
+        }
+        WalEntryType::ActivationUpdate => Ok(None),
+    }
+}
+
 // --- Tests ---

 #[cfg(test)]
@@ -427,6 +526,40 @@ mod tests {
        assert_eq!(entries[2].embedding, vec![5.0, 6.0]);
    }

+    #[test]
+    fn read_len_prefixed_str_rejects_oversized_len_claim() {
+        let dir = TempDir::new().unwrap();
+        let path = dir.path().join("oversized_str.bin");
+        {
+            let mut f = File::create(&path).unwrap();
+            // Claim a length far beyond MAX_WAL_FIELD_LEN; no payload follows.
+            f.write_all(&(u32::MAX).to_le_bytes()).unwrap();
+        }
+        let mut f = File::open(&path).unwrap();
+        let result = read_len_prefixed_str(&mut f);
+        assert!(
+            matches!(result, Err(MemoryError::Schema(_))),
+            "expected a clean Schema error, got {result:?}"
+        );
+    }
+
+    #[test]
+    fn read_embedding_rejects_oversized_count_claim() {
+        let dir = TempDir::new().unwrap();
+        let path = dir.path().join("oversized_embedding.bin");
+        {
+            let mut f = File::create(&path).unwrap();
+            // Claim a count far beyond MAX_WAL_FIELD_LEN / 4; no payload follows.
+            f.write_all(&(u32::MAX).to_le_bytes()).unwrap();
+        }
+        let mut f = File::open(&path).unwrap();
+        let result = read_embedding(&mut f);
+        assert!(
+            matches!(result, Err(MemoryError::Schema(_))),
+            "expected a clean Schema error, got {result:?}"
+        );
+    }
+
    #[test]
    fn test_wal_truncate() {
        let dir = TempDir::new().unwrap();
@@ -749,6 +882,86 @@ mod tests {
        assert!(err.contains("unsupported WAL version"), "got: {err}");
    }

+    #[test]
+    fn test_wal_v2_detects_corrupted_payload_and_stops_replay() {
+        let dir = TempDir::new().unwrap();
+        let wal_path = dir.path().join("test.h5.wal");
+        let mut wal = WalFile::open(&wal_path).unwrap();
+        wal.append_save(&make_wal_entry("first", &[1.0, 2.0]))
+            .unwrap();
+        let len_after_first = std::fs::metadata(&wal_path).unwrap().len();
+        wal.append_save(&make_wal_entry("second", &[3.0, 4.0]))
+            .unwrap();
+        drop(wal);
+
+        // Flip one byte inside the second entry's "second" chunk string
+        // (well past the header and the first entry, and not touching any
+        // length-prefix field) — this must be caught by the CRC32 trailer,
+        // not by any length-cap guard.
+        let mut bytes = std::fs::read(&wal_path).unwrap();
+        let corrupt_at = len_after_first as usize + 15;
+        bytes[corrupt_at] ^= 0xFF;
+        std::fs::write(&wal_path, &bytes).unwrap();
+
+        let entries = WalFile::read_entries(&wal_path).unwrap();
+        assert_eq!(
+            entries.len(),
+            1,
+            "the corrupted second entry must not be returned"
+        );
+        assert_eq!(entries[0].chunk, "first");
+    }
+
+    #[test]
+    fn test_wal_reads_legacy_v1_format_without_crc() {
+        let dir = TempDir::new().unwrap();
+        let wal_path = dir.path().join("legacy.h5.wal");
+        let mut buf = Vec::new();
+        buf.extend_from_slice(&WAL_MAGIC);
+        buf.push(WAL_VERSION_LEGACY_NO_CRC);
+        buf.extend_from_slice(&1u32.to_le_bytes());
+        // One Save entry in the old format: type + timestamp + fields, with
+        // no trailing CRC32.
+        buf.push(WalEntryType::Save as u8);
+        buf.extend_from_slice(&42.0f64.to_le_bytes());
+        serialize_str(&mut buf, "legacy-chunk");
+        let embedding = [1.0f32, 2.0];
+        buf.extend_from_slice(&(embedding.len() as u32).to_le_bytes());
+        for v in embedding {
+            buf.extend_from_slice(&v.to_le_bytes());
+        }
+        serialize_str(&mut buf, "chan");
+        serialize_str(&mut buf, "sess");
+        serialize_str(&mut buf, "tags");
+        std::fs::write(&wal_path, &buf).unwrap();
+
+        let entries = WalFile::read_entries(&wal_path).unwrap();
+        assert_eq!(entries.len(), 1);
+        assert_eq!(entries[0].chunk, "legacy-chunk");
+        assert_eq!(entries[0].embedding, vec![1.0, 2.0]);
+    }
+
+    #[test]
+    fn test_wal_open_migrates_legacy_v1_to_current_version() {
+        let dir = TempDir::new().unwrap();
+        let wal_path = dir.path().join("legacy.h5.wal");
+        let mut buf = Vec::new();
+        buf.extend_from_slice(&WAL_MAGIC);
+        buf.push(WAL_VERSION_LEGACY_NO_CRC);
+        buf.extend_from_slice(&0u32.to_le_bytes());
+        std::fs::write(&wal_path, &buf).unwrap();
+
+        let wal = WalFile::open(&wal_path).unwrap();
+        assert!(wal.is_empty());
+        drop(wal);
+
+        let bytes = std::fs::read(&wal_path).unwrap();
+        assert_eq!(
+            bytes[4], WAL_VERSION,
+            "legacy file must be migrated to the current version"
+        );
+    }
+
    #[test]
    fn test_wal_disabled() {
        let dir = TempDir::new().unwrap();
@@ -80,8 +80,7 @@ fn hnsw_matches_bruteforce_oracle() {
    oracle.sort_by(|a, b| b.1.partial_cmp(&a.1).unwrap());
    let oracle_ids: std::collections::HashSet<usize> =
        oracle.iter().take(k).map(|(i, _)| *i).collect();
-    let hnsw_ids: std::collections::HashSet<usize> =
-        results.iter().map(|r| r.index).collect();
+    let hnsw_ids: std::collections::HashSet<usize> = results.iter().map(|r| r.index).collect();

    let overlap = oracle_ids.intersection(&hnsw_ids).count();
    assert!(
@@ -127,17 +126,19 @@ fn incremental_inserts_after_search_are_found() {
    // First batch, then a search to force the index to build.
    for i in 0..40 {
        let v = make_vector(&mut seed, dim);
-        mem.save(entry(&format!("a{i}"), v, &format!("a{i}"))).unwrap();
+        mem.save(entry(&format!("a{i}"), v, &format!("a{i}")))
+            .unwrap();
    }
    let _ = mem.hybrid_search(&make_vector(&mut seed, dim), "", 1.0, 0.0, 5);

    // Now insert a distinctive vector incrementally and confirm we can find it.
    let needle = vec![10.0f32; dim];
-    let idx = mem
-        .save(entry("needle", needle.clone(), "needle"))
-        .unwrap();
+    let idx = mem.save(entry("needle", needle.clone(), "needle")).unwrap();
    let hits = mem.hybrid_search(&needle, "", 1.0, 0.0, 1);
-    assert_eq!(hits[0].index, idx, "incrementally inserted vector must be found");
+    assert_eq!(
+        hits[0].index, idx,
+        "incrementally inserted vector must be found"
+    );
 }

 #[test]
@@ -158,6 +159,9 @@ fn save_batch_then_search_is_consistent() {
    // Exact-match queries should resolve to themselves after a batch insert.
    for probe in [0usize, 17, 49] {
        let hits = mem.hybrid_search(&vectors[probe], "", 1.0, 0.0, 1);
-        assert_eq!(hits[0].index, probe, "batch-inserted vector {probe} not found");
+        assert_eq!(
+            hits[0].index, probe,
+            "batch-inserted vector {probe} not found"
+        );
    }
 }
@@ -10,3 +10,6 @@ crate-type = ["cdylib"]

 [dependencies]
 clawhdf5-agent = { path = "../clawhdf5-agent", default-features = false }
+
+[dev-dependencies]
+tempfile = { workspace = true }
@@ -3,13 +3,14 @@
 //! Exposes `extern "C"` functions for use via JNI from Kotlin.
 //! Each HDF5Memory instance is managed via an opaque handle (pointer).
 //!
-//! Thread safety: the caller (Kotlin side) must synchronize access
-//! to a single handle. Multiple handles are independent.
+//! Thread safety: each handle wraps `HDF5Memory` in a `Mutex`, so concurrent
+//! calls on the same handle are safe.  Multiple handles are fully independent.

 use std::ffi::{CStr, CString};
 use std::os::raw::c_char;
 use std::path::PathBuf;
 use std::ptr;
+use std::sync::Mutex;

 use clawhdf5_agent::{AgentMemory, HDF5Memory, MemoryConfig, MemoryEntry};

@@ -17,8 +18,12 @@ use clawhdf5_agent::{AgentMemory, HDF5Memory, MemoryConfig, MemoryEntry};
 // Handle management
 // ---------------------------------------------------------------------------

-/// Opaque handle to an HDF5Memory instance.
-type Handle = *mut HDF5Memory;
+/// Opaque handle to a mutex-protected HDF5Memory instance.
+///
+/// Stored on the heap so that the raw pointer (an integer from JNI's
+/// perspective) is stable across calls.  The `Mutex` makes concurrent JNI
+/// calls on the same handle safe without requiring the caller to synchronize.
+type Handle = *mut Mutex<HDF5Memory>;

 /// Create a new HDF5 memory file.
 ///
@@ -46,7 +51,7 @@ pub unsafe extern "C" fn edgehdf5_create(

    let config = MemoryConfig::new(PathBuf::from(path), &agent_id, embedding_dim as usize);
    match HDF5Memory::create(config) {
-        Ok(mem) => Box::into_raw(Box::new(mem)),
+        Ok(mem) => Box::into_raw(Box::new(Mutex::new(mem))),
        Err(_) => ptr::null_mut(),
    }
 }
@@ -67,7 +72,7 @@ pub unsafe extern "C" fn edgehdf5_open(path: *const c_char) -> Handle {
    };

    match HDF5Memory::open(std::path::Path::new(&path)) {
-        Ok(mem) => Box::into_raw(Box::new(mem)),
+        Ok(mem) => Box::into_raw(Box::new(Mutex::new(mem))),
        Err(_) => ptr::null_mut(),
    }
 }
@@ -82,7 +87,7 @@ pub unsafe extern "C" fn edgehdf5_open(path: *const c_char) -> Handle {
 pub unsafe extern "C" fn edgehdf5_close(handle: Handle) {
    if !handle.is_null() {
        // SAFETY: handle was created by Box::into_raw in edgehdf5_create; this is the final use.
-        unsafe { drop(Box::from_raw(handle)) };
+        unsafe { drop(Box::<Mutex<HDF5Memory>>::from_raw(handle)) };
    }
 }

@@ -92,11 +97,18 @@ pub unsafe extern "C" fn edgehdf5_close(handle: Handle) {

 /// Save a memory entry. Returns the entry index, or -1 on failure.
 ///
+/// `embedding_len` is validated against the handle's configured
+/// `embedding_dim` before the input slice is constructed; a mismatch fails
+/// the call with -1 rather than reading out of bounds. This is a length
+/// check only — it cannot detect a same-length buffer that is otherwise
+/// too short or invalid.
+///
 /// # Safety
 ///
 /// - `handle` must be a valid, non-null handle.
 /// - All `*const c_char` arguments must be valid, null-terminated C strings.
-/// - `embedding_ptr` must point to at least `embedding_len` contiguous `f32` values.
+/// - If `embedding_len` matches the handle's `embedding_dim`, `embedding_ptr`
+///   must point to at least that many contiguous, valid `f32` values.
 #[unsafe(no_mangle)]
 pub unsafe extern "C" fn edgehdf5_save(
    handle: Handle,
@@ -108,11 +120,15 @@ pub unsafe extern "C" fn edgehdf5_save(
    session_id: *const c_char,
    tags: *const c_char,
 ) -> i64 {
-    // SAFETY: handle is a valid non-null Handle from edgehdf5_create; caller ensures exclusive access.
-    let mem = match unsafe { handle.as_mut() } {
+    // SAFETY: handle is a valid non-null Handle from edgehdf5_create.
+    let mtx = match unsafe { handle.as_ref() } {
        Some(m) => m,
        None => return -1,
    };
+    let mut mem = match mtx.lock() {
+        Ok(g) => g,
+        Err(_) => return -1,
+    };

    // SAFETY: JNI caller guarantees the pointer argument is a valid null-terminated C string.
    let chunk = match unsafe { cstr_to_string(chunk) } {
@@ -135,8 +151,14 @@ pub unsafe extern "C" fn edgehdf5_save(
        None => return -1,
    };

+    if embedding_ptr.is_null() || embedding_len as usize != mem.config().embedding_dim {
+        return -1;
+    }
    let embedding =
-        // SAFETY: JNI caller guarantees embedding_ptr points to embedding_len valid f32 values.
+        // SAFETY: embedding_ptr is non-null and embedding_len matches the handle's configured
+        // embedding_dim (checked above); JNI caller guarantees it points to that many valid f32
+        // values. A mismatched-but-equal-length short buffer is not caught by this length check
+        // alone — the caller is still responsible for pointer validity.
        unsafe { std::slice::from_raw_parts(embedding_ptr, embedding_len as usize) }.to_vec();

    let entry = MemoryEntry {
@@ -163,7 +185,7 @@ pub unsafe extern "C" fn edgehdf5_save(
 pub unsafe extern "C" fn edgehdf5_count_active(handle: Handle) -> u64 {
    // SAFETY: handle is a valid non-null Handle from edgehdf5_create.
    match unsafe { handle.as_ref() } {
-        Some(mem) => mem.count_active() as u64,
+        Some(mtx) => mtx.lock().map(|g| g.count_active() as u64).unwrap_or(0),
        None => 0,
    }
 }
@@ -177,7 +199,7 @@ pub unsafe extern "C" fn edgehdf5_count_active(handle: Handle) -> u64 {
 pub unsafe extern "C" fn edgehdf5_count(handle: Handle) -> u64 {
    // SAFETY: handle is a valid non-null Handle from edgehdf5_create.
    match unsafe { handle.as_ref() } {
-        Some(mem) => mem.count() as u64,
+        Some(mtx) => mtx.lock().map(|g| g.count() as u64).unwrap_or(0),
        None => 0,
    }
 }
@@ -189,11 +211,15 @@ pub unsafe extern "C" fn edgehdf5_count(handle: Handle) -> u64 {
 /// `handle` must be a valid, non-null handle.
 #[unsafe(no_mangle)]
 pub unsafe extern "C" fn edgehdf5_delete(handle: Handle, index: u64) -> i32 {
-    // SAFETY: handle is a valid non-null Handle from edgehdf5_create; caller ensures exclusive access.
-    let mem = match unsafe { handle.as_mut() } {
+    // SAFETY: handle is a valid non-null Handle from edgehdf5_create.
+    let mtx = match unsafe { handle.as_ref() } {
        Some(m) => m,
        None => return -1,
    };
+    let mut mem = match mtx.lock() {
+        Ok(g) => g,
+        Err(_) => return -1,
+    };

    match mem.delete(index as usize) {
        Ok(()) => 0,
@@ -210,11 +236,18 @@ pub unsafe extern "C" fn edgehdf5_delete(handle: Handle, index: u64) -> i32 {
 /// Performs hybrid search and writes up to `max_results` entries into the
 /// provided output arrays. Returns the number of results written.
 ///
+/// `query_embedding_len` is validated against the handle's configured
+/// `embedding_dim` before the input slice is constructed; a mismatch fails
+/// the call (returns 0) rather than reading out of bounds. This is a length
+/// check only — it cannot detect a same-length buffer that is otherwise too
+/// short or invalid.
+///
 /// # Safety
 ///
 /// - `handle` must be a valid, non-null handle.
 /// - `query_text` must be a valid, null-terminated C string.
-/// - `query_embedding_ptr` must point to at least `query_embedding_len` `f32` values.
+/// - If `query_embedding_len` matches the handle's `embedding_dim`,
+///   `query_embedding_ptr` must point to at least that many valid `f32` values.
 /// - `out_indices` and `out_scores` must point to arrays of at least `max_results` elements.
 /// - `out_chunks` must be null or point to an array of at least `max_results` pointers.
 #[unsafe(no_mangle)]
@@ -230,18 +263,28 @@ pub unsafe extern "C" fn edgehdf5_hybrid_search(
    out_scores: *mut f32,
    out_chunks: *mut *mut c_char,
 ) -> u32 {
-    // SAFETY: handle is a valid non-null Handle from edgehdf5_create; caller ensures exclusive access.
-    let mem = match unsafe { handle.as_mut() } {
+    // SAFETY: handle is a valid non-null Handle from edgehdf5_create.
+    let mtx = match unsafe { handle.as_ref() } {
        Some(m) => m,
        None => return 0,
    };
+    let mut mem = match mtx.lock() {
+        Ok(g) => g,
+        Err(_) => return 0,
+    };
    // SAFETY: JNI caller guarantees the pointer argument is a valid null-terminated C string.
    let query_text = match unsafe { cstr_to_string(query_text) } {
        Some(s) => s,
        None => return 0,
    };
+    if query_embedding_ptr.is_null() || query_embedding_len as usize != mem.config().embedding_dim {
+        return 0;
+    }
    let query_embedding =
-        // SAFETY: JNI caller guarantees query_embedding_ptr points to query_embedding_len valid f32 values.
+        // SAFETY: query_embedding_ptr is non-null and query_embedding_len matches the handle's
+        // configured embedding_dim (checked above); JNI caller guarantees it points to that many
+        // valid f32 values. A mismatched-but-equal-length short buffer is not caught by this
+        // length check alone — the caller is still responsible for pointer validity.
        unsafe { std::slice::from_raw_parts(query_embedding_ptr, query_embedding_len as usize) };

    let results = mem.hybrid_search(
@@ -303,11 +346,15 @@ pub unsafe extern "C" fn edgehdf5_add_session(
    channel: *const c_char,
    summary: *const c_char,
 ) -> i32 {
-    // SAFETY: handle is a valid non-null Handle from edgehdf5_create; caller ensures exclusive access.
-    let mem = match unsafe { handle.as_mut() } {
+    // SAFETY: handle is a valid non-null Handle from edgehdf5_create.
+    let mtx = match unsafe { handle.as_ref() } {
        Some(m) => m,
        None => return -1,
    };
+    let mut mem = match mtx.lock() {
+        Ok(g) => g,
+        Err(_) => return -1,
+    };
    // SAFETY: JNI caller guarantees the pointer argument is a valid null-terminated C string.
    let id = match unsafe { cstr_to_string(id) } {
        Some(s) => s,
@@ -349,10 +396,14 @@ pub unsafe extern "C" fn edgehdf5_get_session_summary(
    session_id: *const c_char,
 ) -> *mut c_char {
    // SAFETY: handle is a valid non-null Handle from edgehdf5_create.
-    let mem = match unsafe { handle.as_ref() } {
+    let mtx = match unsafe { handle.as_ref() } {
        Some(m) => m,
        None => return ptr::null_mut(),
    };
+    let mem = match mtx.lock() {
+        Ok(g) => g,
+        Err(_) => return ptr::null_mut(),
+    };
    // SAFETY: JNI caller guarantees the pointer argument is a valid null-terminated C string.
    let session_id = match unsafe { cstr_to_string(session_id) } {
        Some(s) => s,
@@ -385,11 +436,15 @@ pub unsafe extern "C" fn edgehdf5_add_entity(
    entity_type: *const c_char,
    embedding_idx: i64,
 ) -> i64 {
-    // SAFETY: handle is a valid non-null Handle from edgehdf5_create; caller ensures exclusive access.
-    let mem = match unsafe { handle.as_mut() } {
+    // SAFETY: handle is a valid non-null Handle from edgehdf5_create.
+    let mtx = match unsafe { handle.as_ref() } {
        Some(m) => m,
        None => return -1,
    };
+    let mut mem = match mtx.lock() {
+        Ok(g) => g,
+        Err(_) => return -1,
+    };
    // SAFETY: JNI caller guarantees the pointer argument is a valid null-terminated C string.
    let name = match unsafe { cstr_to_string(name) } {
        Some(s) => s,
@@ -421,11 +476,15 @@ pub unsafe extern "C" fn edgehdf5_add_relation(
    relation: *const c_char,
    weight: f32,
 ) -> i32 {
-    // SAFETY: handle is a valid non-null Handle from edgehdf5_create; caller ensures exclusive access.
-    let mem = match unsafe { handle.as_mut() } {
+    // SAFETY: handle is a valid non-null Handle from edgehdf5_create.
+    let mtx = match unsafe { handle.as_ref() } {
        Some(m) => m,
        None => return -1,
    };
+    let mut mem = match mtx.lock() {
+        Ok(g) => g,
+        Err(_) => return -1,
+    };
    // SAFETY: JNI caller guarantees the pointer argument is a valid null-terminated C string.
    let relation = match unsafe { cstr_to_string(relation) } {
        Some(s) => s,
@@ -456,3 +515,153 @@ unsafe fn cstr_to_string(ptr: *const c_char) -> Option<String> {
        .ok()
        .map(String::from)
 }
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    const EMBEDDING_DIM: u32 = 4;
+
+    fn open_handle(dir: &tempfile::TempDir) -> Handle {
+        let path = CString::new(dir.path().join("mem.h5").to_str().unwrap()).unwrap();
+        let agent_id = CString::new("test-agent").unwrap();
+        // SAFETY: both C strings are valid and null-terminated; returned handle
+        // wraps HDF5Memory in a Mutex and is safe to use from multiple threads.
+        unsafe { edgehdf5_create(path.as_ptr(), agent_id.as_ptr(), EMBEDDING_DIM) }
+    }
+
+    #[test]
+    fn save_rejects_mismatched_embedding_len() {
+        let dir = tempfile::tempdir().unwrap();
+        let handle = open_handle(&dir);
+        assert!(!handle.is_null());
+
+        let embedding = [1.0f32, 2.0, 3.0]; // len 3, dim is 4
+        let chunk = CString::new("hello").unwrap();
+        let channel = CString::new("test").unwrap();
+        let session = CString::new("s1").unwrap();
+        let tags = CString::new("").unwrap();
+
+        // SAFETY: handle is valid; all C strings are valid; embedding_len (3) intentionally
+        // does not match embedding_dim (4), which edgehdf5_save must reject before touching
+        // embedding_ptr.
+        let result = unsafe {
+            edgehdf5_save(
+                handle,
+                chunk.as_ptr(),
+                embedding.as_ptr(),
+                embedding.len() as u32,
+                channel.as_ptr(),
+                0.0,
+                session.as_ptr(),
+                tags.as_ptr(),
+            )
+        };
+        assert_eq!(result, -1, "mismatched embedding_len must be rejected");
+
+        unsafe { edgehdf5_close(handle) };
+    }
+
+    #[test]
+    fn save_rejects_null_embedding_ptr() {
+        let dir = tempfile::tempdir().unwrap();
+        let handle = open_handle(&dir);
+        assert!(!handle.is_null());
+
+        let chunk = CString::new("hello").unwrap();
+        let channel = CString::new("test").unwrap();
+        let session = CString::new("s1").unwrap();
+        let tags = CString::new("").unwrap();
+
+        // SAFETY: handle and C strings are valid; embedding_ptr is intentionally null, which
+        // edgehdf5_save must reject before constructing a slice from it.
+        let result = unsafe {
+            edgehdf5_save(
+                handle,
+                chunk.as_ptr(),
+                ptr::null(),
+                EMBEDDING_DIM,
+                channel.as_ptr(),
+                0.0,
+                session.as_ptr(),
+                tags.as_ptr(),
+            )
+        };
+        assert_eq!(result, -1, "null embedding_ptr must be rejected");
+
+        unsafe { edgehdf5_close(handle) };
+    }
+
+    #[test]
+    fn hybrid_search_rejects_mismatched_embedding_len() {
+        let dir = tempfile::tempdir().unwrap();
+        let handle = open_handle(&dir);
+        assert!(!handle.is_null());
+
+        let query_embedding = [1.0f32, 2.0]; // len 2, dim is 4
+        let query_text = CString::new("hello").unwrap();
+        let mut out_indices = [0u64; 4];
+        let mut out_scores = [0.0f32; 4];
+
+        // SAFETY: handle and query_text are valid; query_embedding_len (2) intentionally does
+        // not match embedding_dim (4), which edgehdf5_hybrid_search must reject before touching
+        // query_embedding_ptr. Output buffers are sized to max_results.
+        let count = unsafe {
+            edgehdf5_hybrid_search(
+                handle,
+                query_embedding.as_ptr(),
+                query_embedding.len() as u32,
+                query_text.as_ptr(),
+                0.7,
+                0.3,
+                4,
+                out_indices.as_mut_ptr(),
+                out_scores.as_mut_ptr(),
+                ptr::null_mut(),
+            )
+        };
+        assert_eq!(count, 0, "mismatched query_embedding_len must be rejected");
+
+        unsafe { edgehdf5_close(handle) };
+    }
+
+    /// Verify that concurrent calls on the same handle do not cause data races.
+    ///
+    /// Each thread calls `edgehdf5_count_active` on the shared handle.  With the
+    /// `Mutex` wrapper in place this must complete without a panic or SIGABRT.
+    /// Without the mutex it would be UB.
+    #[test]
+    fn concurrent_count_active_is_safe() {
+        use std::sync::Arc;
+
+        let dir = tempfile::tempdir().unwrap();
+        let handle = open_handle(&dir);
+        assert!(!handle.is_null());
+
+        // Share the raw pointer across threads via a copy-friendly wrapper.
+        // SAFETY: the Mutex inside the handle makes concurrent access sound.
+        #[derive(Clone, Copy)]
+        struct SendableHandle(Handle);
+        unsafe impl Send for SendableHandle {}
+        // SAFETY: the Mutex inside the handle serialises all access,
+        // so sharing the wrapper across threads is sound.
+        unsafe impl Sync for SendableHandle {}
+
+        let shared = Arc::new(SendableHandle(handle));
+        let threads: Vec<_> = (0..8)
+            .map(|_| {
+                let h = Arc::clone(&shared);
+                std::thread::spawn(move || {
+                    // SAFETY: handle is valid (not yet closed); Mutex guards access.
+                    let count = unsafe { edgehdf5_count_active(h.0) };
+                    assert_eq!(count, 0);
+                })
+            })
+            .collect();
+        for t in threads {
+            t.join().expect("thread panicked");
+        }
+
+        unsafe { edgehdf5_close(handle) };
+    }
+}
@@ -12,3 +12,7 @@ categories = ["algorithms", "science"]
 [dependencies]
 clawhdf5-format = { path = "../clawhdf5-format", version = "2.1.0" }
 clawhdf5-io = { path = "../clawhdf5-io", version = "2.1.0" }
+rayon = { version = "1", optional = true }
+
+[features]
+parallel = ["rayon"]
@@ -379,7 +379,13 @@ impl HnswIndex {

        // Phase 1: greedy descent from the top down to node_level + 1.
        for layer in (node_level + 1..=ep_level).rev() {
-            ep = greedy_closest(&self.vectors, &self.graph[layer], &self.vectors[id], ep, self.metric);
+            ep = greedy_closest(
+                &self.vectors,
+                &self.graph[layer],
+                &self.vectors[id],
+                ep,
+                self.metric,
+            );
        }

        // Phase 2: search and connect from min(node_level, ep_level) down to 0.
@@ -733,12 +739,190 @@ impl HnswIndex {
    pub fn m_max0(&self) -> usize {
        self.m_max0
    }
+
+    /// Insert a batch of vectors efficiently.
+    ///
+    /// With the `parallel` feature enabled, neighbor searches for each new
+    /// vector are executed concurrently against the graph state *before* the
+    /// batch is applied, then edges are wired serially. This trades a small
+    /// reduction in intra-batch connectivity for significant wall-clock
+    /// speedup on large batches.
+    ///
+    /// Without the `parallel` feature, this is equivalent to calling
+    /// [`HnswIndex::insert`] for each vector in order.
+    ///
+    /// Returns the assigned IDs in insertion order.
+    pub fn batch_insert(&mut self, vectors: Vec<Vec<f32>>) -> Vec<usize> {
+        if vectors.is_empty() {
+            return Vec::new();
+        }
+
+        // Empty index: fall through to serial insert so the entry-point
+        // seeding logic in `insert` runs correctly.
+        if self.vectors.is_empty() {
+            return vectors
+                .into_iter()
+                .map(|v| self.insert(v))
+                .collect();
+        }
+
+        let dim = self.vectors[0].len();
+        for v in &vectors {
+            assert_eq!(v.len(), dim, "batch_insert dimension mismatch");
+        }
+
+        let base_id = self.vectors.len();
+        let n = vectors.len();
+
+        // Pre-assign levels to all incoming vectors.
+        let node_levels: Vec<usize> = (0..n)
+            .map(|i| assign_level(base_id + i, self.m))
+            .collect();
+
+        // Phase 1 — neighbor search (read-only on the current graph state).
+        // Returns, for each new vector, the list of (layer, selected_neighbors)
+        // pairs that will become its initial edge set.
+        let per_vector_neighbors: Vec<Vec<(usize, Vec<usize>)>> =
+            self.find_neighbors_batch(&vectors, &node_levels);
+
+        // Phase 2 — extend the vector store (serial).
+        self.vectors.extend(vectors);
+        self.deleted.extend(std::iter::repeat(false).take(n));
+        self.node_levels.extend_from_slice(&node_levels);
+
+        // Grow existing layers to accommodate the new node slots.
+        for layer in self.graph.iter_mut() {
+            layer.resize(self.vectors.len(), Vec::new());
+        }
+        // Add any brand-new top layers introduced by this batch.
+        let new_max_level = node_levels.iter().copied().max().unwrap_or(0);
+        while self.graph.len() <= new_max_level {
+            self.graph.push(vec![Vec::new(); self.vectors.len()]);
+        }
+
+        // Phase 3 — wire edges and track entry-point promotions (serial).
+        for (batch_idx, layer_neighbors) in per_vector_neighbors.into_iter().enumerate() {
+            let id = base_id + batch_idx;
+            for (layer, selected) in layer_neighbors {
+                let max_conn = if layer == 0 { self.m_max0 } else { self.m };
+                self.graph[layer][id] = selected.clone();
+                for &nb in &selected {
+                    self.graph[layer][nb].push(id);
+                    if self.graph[layer][nb].len() > max_conn {
+                        prune_connections(
+                            &self.vectors,
+                            &mut self.graph[layer][nb],
+                            nb,
+                            max_conn,
+                            self.metric,
+                        );
+                    }
+                }
+            }
+            // Promote entry point if this node sits on a taller layer.
+            let ep_level = self.node_levels[self.entry_point];
+            if node_levels[batch_idx] > ep_level {
+                self.entry_point = id;
+            }
+        }
+
+        (base_id..base_id + n).collect()
+    }
+
+    /// Search for neighbors of each vector in `vectors` against the current
+    /// (read-only) graph. Returns per-vector `(layer_id, neighbor_ids)` pairs.
+    fn find_neighbors_batch(
+        &self,
+        vectors: &[Vec<f32>],
+        node_levels: &[usize],
+    ) -> Vec<Vec<(usize, Vec<usize>)>> {
+        let ep_level = self.node_levels[self.entry_point];
+        let entry_point = self.entry_point;
+
+        #[cfg(feature = "parallel")]
+        {
+            use rayon::prelude::*;
+            let existing = &self.vectors;
+            let graph = &self.graph;
+            let metric = self.metric;
+            let m = self.m;
+            let m_max0 = self.m_max0;
+            let ef = self.ef_construction;
+            vectors
+                .par_iter()
+                .zip(node_levels.par_iter())
+                .map(|(v, &nl)| {
+                    find_neighbors_for(
+                        existing, graph, v, nl, ep_level, entry_point, m, m_max0, ef, metric,
+                    )
+                })
+                .collect()
+        }
+        #[cfg(not(feature = "parallel"))]
+        {
+            vectors
+                .iter()
+                .zip(node_levels.iter())
+                .map(|(v, &nl)| {
+                    find_neighbors_for(
+                        &self.vectors,
+                        &self.graph,
+                        v,
+                        nl,
+                        ep_level,
+                        entry_point,
+                        self.m,
+                        self.m_max0,
+                        self.ef_construction,
+                        self.metric,
+                    )
+                })
+                .collect()
+        }
+    }
 }

 // ---------------------------------------------------------------------------
 // Internal HNSW algorithms
 // ---------------------------------------------------------------------------

+/// Compute the set of neighbor edges for `new_vec` against a read-only snapshot
+/// of the existing graph. Used by [`HnswIndex::batch_insert`].
+#[allow(clippy::too_many_arguments)]
+fn find_neighbors_for(
+    existing: &[Vec<f32>],
+    graph: &[Vec<Vec<usize>>],
+    new_vec: &[f32],
+    node_level: usize,
+    ep_level: usize,
+    entry_point: usize,
+    m: usize,
+    m_max0: usize,
+    ef: usize,
+    metric: DistanceMetric,
+) -> Vec<(usize, Vec<usize>)> {
+    let mut ep = entry_point;
+
+    // Phase 1: greedy descent from the top layer down to node_level + 1.
+    for layer in (node_level + 1..=ep_level).rev() {
+        ep = greedy_closest(existing, &graph[layer], new_vec, ep, metric);
+    }
+
+    // Phase 2: beam search at each layer, collecting selected neighbors.
+    let bottom = node_level.min(ep_level);
+    let mut result = Vec::with_capacity(bottom + 1);
+    for layer in (0..=bottom).rev() {
+        let max_conn = if layer == 0 { m_max0 } else { m };
+        let candidates = search_layer(existing, &graph[layer], new_vec, ep, ef, metric);
+        let selected: Vec<usize> = candidates.iter().take(max_conn).map(|c| c.id).collect();
+        if !selected.is_empty() {
+            ep = selected[0];
+        }
+        result.push((layer, selected));
+    }
+    result
+}
+
 /// Greedy search: find the single closest node to `query` starting from `ep`.
 fn greedy_closest(
    vectors: &[Vec<f32>],
@@ -851,6 +1035,15 @@ fn prune_connections(
    if neighbors.len() <= max_conn {
        return;
    }
+    #[cfg(feature = "parallel")]
+    let mut scored: Vec<(usize, f32)> = {
+        use rayon::prelude::*;
+        neighbors
+            .par_iter()
+            .map(|&n| (n, compute_distance(&vectors[node], &vectors[n], metric)))
+            .collect()
+    };
+    #[cfg(not(feature = "parallel"))]
    let mut scored: Vec<(usize, f32)> = neighbors
        .iter()
        .map(|&n| (n, compute_distance(&vectors[node], &vectors[n], metric)))
@@ -1012,11 +1205,14 @@ fn get_attr_i64(attrs: &[(String, AttrValue)], name: &str) -> Result<i64, Format
 /// Like [`get_attr_i64`] but returns `None` when the attribute is absent or not
 /// an integer, instead of erroring. Used for optional/back-compat attributes.
 fn get_attr_i64_opt(attrs: &[(String, AttrValue)], name: &str) -> Option<i64> {
-    attrs.iter().find(|(n, _)| n == name).and_then(|(_, v)| match v {
-        AttrValue::I64(val) => Some(*val),
-        AttrValue::U64(val) => Some(*val as i64),
-        _ => None,
-    })
+    attrs
+        .iter()
+        .find(|(n, _)| n == name)
+        .and_then(|(_, v)| match v {
+            AttrValue::I64(val) => Some(*val),
+            AttrValue::U64(val) => Some(*val as i64),
+            _ => None,
+        })
 }

 fn get_attr_string(attrs: &[(String, AttrValue)], name: &str) -> Result<String, FormatError> {
@@ -1434,4 +1630,75 @@ mod tests {
        assert_eq!(results.len(), 3);
        assert_eq!(results[0].0, 0);
    }
+
+    #[test]
+    fn batch_insert_ids_are_sequential() {
+        let vectors = make_random_vectors(20, 8, 42);
+        let mut index = HnswIndex::new(8, 32, DistanceMetric::L2);
+        let ids = index.batch_insert(vectors.clone());
+        assert_eq!(ids, (0..20).collect::<Vec<_>>());
+        assert_eq!(index.len(), 20);
+    }
+
+    #[test]
+    fn batch_insert_into_existing_index() {
+        let first = make_random_vectors(10, 8, 11);
+        let second = make_random_vectors(10, 8, 22);
+        let mut index = HnswIndex::new(8, 32, DistanceMetric::L2);
+        let ids1 = index.batch_insert(first);
+        assert_eq!(ids1, (0..10).collect::<Vec<_>>());
+        let ids2 = index.batch_insert(second.clone());
+        assert_eq!(ids2, (10..20).collect::<Vec<_>>());
+        assert_eq!(index.len(), 20);
+    }
+
+    #[test]
+    fn batch_insert_search_quality() {
+        // Build index from 50 vectors using serial insert, then build the same
+        // index using batch_insert.  The search results should be identical for
+        // the first 50 vectors (which are fully connected in both cases).
+        let vectors = make_random_vectors(50, 16, 99);
+        let mut serial = HnswIndex::new(8, 32, DistanceMetric::Cosine);
+        for v in &vectors {
+            serial.insert(v.clone());
+        }
+        let mut batch = HnswIndex::new(8, 32, DistanceMetric::Cosine);
+        batch.batch_insert(vectors.clone());
+        assert_eq!(batch.len(), serial.len());
+
+        // Both indexes should find the same nearest neighbor for each query.
+        let queries = make_random_vectors(5, 16, 777);
+        for q in &queries {
+            let s = serial.search(q, 1, 32);
+            let b = batch.search(q, 1, 32);
+            assert!(!s.is_empty() && !b.is_empty());
+            // Result must be in the top-3 of the serial index — batch
+            // is slightly less connected due to the read-snapshot approach.
+            let top3_serial: Vec<usize> = serial.search(q, 3, 32).into_iter().map(|(id, _)| id).collect();
+            assert!(top3_serial.contains(&b[0].0), "batch top-1 not in serial top-3");
+        }
+    }
+
+    #[test]
+    fn batch_insert_empty_is_noop() {
+        let mut index = HnswIndex::new(8, 32, DistanceMetric::L2);
+        let ids = index.batch_insert(vec![]);
+        assert!(ids.is_empty());
+        assert!(index.is_empty());
+    }
+
+    #[test]
+    fn batch_insert_saves_and_loads() {
+        let vectors = make_random_vectors(30, 6, 55);
+        let mut index = HnswIndex::new(8, 32, DistanceMetric::L2);
+        index.batch_insert(vectors.clone());
+        let bytes = index.to_hdf5_bytes().unwrap();
+        let loaded = HnswIndex::load_from_hdf5(&bytes).unwrap();
+        assert_eq!(loaded.len(), 30);
+        assert_eq!(loaded.metric(), DistanceMetric::L2);
+        // The query's own vector should be the nearest neighbor.
+        let q = &vectors[0];
+        let results = loaded.search(q, 1, 32);
+        assert_eq!(results[0].0, 0);
+    }
 }
@@ -50,19 +50,31 @@ harness = false
 clawhdf5-agent = { path = "../clawhdf5-agent" }
 clawhdf5-io = { path = "../clawhdf5-io" }
 mpi = { version = "0.8", optional = true }
-serde = { version = "1", features = ["derive"] }
+serde = { workspace = true }
 serde_json = "1"
-tempfile = "3"
+tempfile = { workspace = true }
 # Optional: libhdf5 C wrapper for side-by-side comparison (requires system libhdf5).
 # Enable with: cargo bench -p clawhdf5-bench --features libhdf5-compare
 # Uses hdf5-metno (fork of hdf5 crate) which supports HDF5 1.14.x.
 hdf5 = { version = "0.12", optional = true, package = "hdf5-metno" }
+# Optional: real sentence embeddings for the LongMemEval bench's vector stage.
+# Enable with: cargo run --release --bin longmemeval_bench --features embeddings
+# Off by default — nothing in the shipped crates depends on these.
+candle-core = { version = "0.9", optional = true }
+candle-nn = { version = "0.9", optional = true }
+candle-transformers = { version = "0.9", optional = true }
+tokenizers = { version = "0.21", optional = true }

 [dev-dependencies]
 clawhdf5 = { path = "../clawhdf5", features = ["zstd", "pcodec"] }
-criterion = { version = "0.5", features = ["html_reports"] }
+criterion = { workspace = true }

 [features]
 # When enabled, benchmarks add matching libhdf5 variants for side-by-side comparison.
 libhdf5-compare = ["hdf5"]
 mpi-io = ["clawhdf5-io/mpi-io", "mpi"]
+# Real MiniLM embeddings for longmemeval_bench, so the vector stage is not inert.
+embeddings = ["candle-core", "candle-nn", "candle-transformers", "tokenizers"]
+# CUDA-accelerated embedding. MiniLM on a CPU takes hours over the full
+# longmemeval_s haystack; on a GPU it is minutes.
+embeddings-cuda = ["embeddings", "candle-core/cuda", "candle-nn/cuda", "candle-transformers/cuda"]
@@ -41,11 +41,7 @@ fn bench_metadata_attrs_write(c: &mut Criterion) {
            let path = tmp.path().join("attrs_libhdf5.h5");
            b.iter(|| {
                let file = hdf5::File::create(&path).unwrap();
-                let ds = file
-                    .new_dataset::<f64>()
-                    .shape([3])
-                    .create("data")
-                    .unwrap();
+                let ds = file.new_dataset::<f64>().shape([3]).create("data").unwrap();
                ds.write(&[1.0f64, 2.0, 3.0]).unwrap();
                for i in 0..k {
                    ds.new_attr::<i64>()
@@ -258,11 +254,7 @@ fn bench_metadata_open_from_disk(c: &mut Criterion) {
        let libhdf5_path = tmp.path().join("open_libhdf5.h5");
        {
            let file = hdf5::File::create(&libhdf5_path).unwrap();
-            let ds = file
-                .new_dataset::<f64>()
-                .shape([3])
-                .create("data")
-                .unwrap();
+            let ds = file.new_dataset::<f64>().shape([3]).create("data").unwrap();
            ds.write(&[1.0f64, 2.0, 3.0]).unwrap();
            ds.new_attr::<i64>()
                .create("label")
@@ -307,13 +299,17 @@ fn bench_metadata_parse_in_memory(c: &mut Criterion) {
        fb.finish().unwrap()
    };

-    group.bench_with_input(BenchmarkId::new("clawhdf5", "in_memory"), &bytes, |b, raw| {
-        b.iter(|| {
-            let file = File::from_bytes(raw.clone()).unwrap();
-            let ds = file.dataset("data").unwrap();
-            ds.attrs().unwrap()
-        });
-    });
+    group.bench_with_input(
+        BenchmarkId::new("clawhdf5", "in_memory"),
+        &bytes,
+        |b, raw| {
+            b.iter(|| {
+                let file = File::from_bytes(raw.clone()).unwrap();
+                let ds = file.dataset("data").unwrap();
+                ds.attrs().unwrap()
+            });
+        },
+    );

    group.finish();
 }
@@ -74,11 +74,7 @@ fn bench_read_sequential(c: &mut Criterion) {
            let data: Vec<f32> = (0..nn).map(|i| i as f32 * 0.001).collect();
            {
                let lf = hdf5::File::create(&path).unwrap();
-                let lds = lf
-                    .new_dataset::<f32>()
-                    .shape([nn])
-                    .create("data")
-                    .unwrap();
+                let lds = lf.new_dataset::<f32>().shape([nn]).create("data").unwrap();
                lds.write(data.as_slice()).unwrap();
            }
            b.iter(|| {
@@ -235,19 +231,23 @@ fn bench_read_zerocopy_mmap(c: &mut Criterion) {

        group.throughput(Throughput::Bytes((n * size_of::<f64>()) as u64));

-        group.bench_with_input(BenchmarkId::new("clawhdf5_mmap_zerocopy", n), &path, |b, p| {
-            b.iter(|| {
-                let file = MmapFile::open(p).unwrap();
-                let ds = file.dataset("data").unwrap();
-                let slice = ds.read_f64_zerocopy().unwrap();
-                // Sum every element to force the mapped pages to actually be
-                // faulted in — returning just `.len()` would measure nothing
-                // but the mmap() syscall, repeating the exact "too-fast-to-
-                // be-real" mistake this benchmark exists to fix.
-                let sum: f64 = slice.map(|s| s.iter().sum()).unwrap_or(0.0);
-                criterion::black_box(sum)
-            });
-        });
+        group.bench_with_input(
+            BenchmarkId::new("clawhdf5_mmap_zerocopy", n),
+            &path,
+            |b, p| {
+                b.iter(|| {
+                    let file = MmapFile::open(p).unwrap();
+                    let ds = file.dataset("data").unwrap();
+                    let slice = ds.read_f64_zerocopy().unwrap();
+                    // Sum every element to force the mapped pages to actually be
+                    // faulted in — returning just `.len()` would measure nothing
+                    // but the mmap() syscall, repeating the exact "too-fast-to-
+                    // be-real" mistake this benchmark exists to fix.
+                    let sum: f64 = slice.map(|s| s.iter().sum()).unwrap_or(0.0);
+                    criterion::black_box(sum)
+                });
+            },
+        );

        group.bench_with_input(BenchmarkId::new("clawhdf5_copy", n), &path, |b, p| {
            b.iter(|| {
@@ -63,11 +63,8 @@ fn bench_write_2d_chunked(c: &mut Criterion) {
    let mut group = c.benchmark_group("write_2d_chunked");

    // (rows, cols, chunk_rows, chunk_cols)
-    let configs: &[(usize, usize, u64, u64)] = &[
-        (32, 32, 8, 32),
-        (128, 128, 32, 128),
-        (512, 512, 64, 512),
-    ];
+    let configs: &[(usize, usize, u64, u64)] =
+        &[(32, 32, 8, 32), (128, 128, 32, 128), (512, 512, 64, 512)];

    for &(rows, cols, cr, cc) in configs {
        let n = rows * cols;
@@ -120,11 +117,8 @@ fn bench_write_2d_chunked(c: &mut Criterion) {
 fn bench_write_2d_chunked_zstd(c: &mut Criterion) {
    let mut group = c.benchmark_group("write_2d_chunked_zstd");

-    let configs: &[(usize, usize, u64, u64)] = &[
-        (32, 32, 8, 32),
-        (128, 128, 32, 128),
-        (512, 512, 64, 512),
-    ];
+    let configs: &[(usize, usize, u64, u64)] =
+        &[(32, 32, 8, 32), (128, 128, 32, 128), (512, 512, 64, 512)];

    for &(rows, cols, cr, cc) in configs {
        let n = rows * cols;
@@ -132,19 +126,23 @@ fn bench_write_2d_chunked_zstd(c: &mut Criterion) {
        let label = format!("{rows}x{cols}");
        group.throughput(Throughput::Bytes((n * size_of::<f32>()) as u64));

-        group.bench_with_input(BenchmarkId::new("clawhdf5/zstd-3", &label), &data, |b, d| {
-            let tmp = TempDir::new().unwrap();
-            let path = tmp.path().join("write_2d_chunked_zstd.h5");
-            b.iter(|| {
-                let mut fb = FileBuilder::new();
-                fb.create_dataset("matrix")
-                    .with_f32_data(d)
-                    .with_shape(&[rows as u64, cols as u64])
-                    .with_chunks(&[cr, cc])
-                    .with_zstd(3);
-                fb.write(&path).unwrap();
-            });
-        });
+        group.bench_with_input(
+            BenchmarkId::new("clawhdf5/zstd-3", &label),
+            &data,
+            |b, d| {
+                let tmp = TempDir::new().unwrap();
+                let path = tmp.path().join("write_2d_chunked_zstd.h5");
+                b.iter(|| {
+                    let mut fb = FileBuilder::new();
+                    fb.create_dataset("matrix")
+                        .with_f32_data(d)
+                        .with_shape(&[rows as u64, cols as u64])
+                        .with_chunks(&[cr, cc])
+                        .with_zstd(3);
+                    fb.write(&path).unwrap();
+                });
+            },
+        );

        group.bench_with_input(
            BenchmarkId::new("clawhdf5/deflate-6", &label),
@@ -178,11 +176,8 @@ fn bench_write_2d_chunked_zstd(c: &mut Criterion) {
 fn bench_write_2d_chunked_pcodec(c: &mut Criterion) {
    let mut group = c.benchmark_group("write_2d_chunked_pcodec");

-    let configs: &[(usize, usize, u64, u64)] = &[
-        (32, 32, 8, 32),
-        (128, 128, 32, 128),
-        (512, 512, 64, 512),
-    ];
+    let configs: &[(usize, usize, u64, u64)] =
+        &[(32, 32, 8, 32), (128, 128, 32, 128), (512, 512, 64, 512)];

    for &(rows, cols, cr, cc) in configs {
        let n = rows * cols;
@@ -0,0 +1,95 @@
+//! World-model sample-loading benchmark — clawhdf5 vs the h5py counterpart.
+//!
+//! Reproduces the access pattern of `stable-worldmodel`'s HDF5 dataloader
+//! (arXiv 2605.21800): a dataset of `(N, H, W, C)` uint8 observation frames,
+//! read one frame at a time in shuffled (dataloader) order. That paper
+//! reports generic HDF5 at 1,416–1,474 samples/s (vs Lance 4,815); this
+//! measures clawhdf5 and h5py on the **same machine and file**, so the
+//! comparison is hardware-controlled. Absolute numbers are not comparable to
+//! the paper's (different box, smaller frames, no torch/transform) — only
+//! clawhdf5-vs-h5py *here* is.
+//!
+//! clawhdf5 mmaps the file once and takes a zero-copy `&[u8]` over the
+//! contiguous observation dataset; frame `i` is a subslice, and the OS pages
+//! it in on access. Two modes, because fairness demands both:
+//!   * default: sum the frame bytes through the zero-copy view — clawhdf5's
+//!     real advantage, no per-frame allocation;
+//!   * `--copy`: `to_vec()` each frame first, matching h5py's unavoidable
+//!     per-frame numpy materialization, so the two do equal work.
+//!
+//! Usage: `... --example worldmodel_sampling -- <file.h5> [passes] [--copy]`
+
+use std::hint::black_box;
+use std::time::Instant;
+
+use clawhdf5::MmapFile;
+
+fn main() {
+    let args: Vec<String> = std::env::args().collect();
+    let path = args
+        .get(1)
+        .expect("usage: worldmodel_sampling <file.h5> [passes] [--copy]");
+    let passes: usize = args.get(2).and_then(|s| s.parse().ok()).unwrap_or(5);
+    let copy = args.iter().any(|a| a == "--copy");
+
+    let file = MmapFile::open(path).expect("open");
+    let ds = file.dataset("observation").expect("observation dataset");
+    let shape = ds.shape().expect("shape");
+    let n = shape[0] as usize;
+    let frame_bytes: usize = shape[1..].iter().map(|&d| d as usize).product();
+    let raw = ds
+        .read_raw_slice()
+        .expect("read_raw_slice")
+        .expect("contiguous zero-copy slice");
+    assert_eq!(raw.len(), n * frame_bytes, "unexpected dataset size");
+
+    let order = shuffled(n);
+
+    let touch = |slice: &[u8]| -> u64 {
+        if copy {
+            let owned = slice.to_vec();
+            owned.iter().map(|&b| u64::from(b)).sum()
+        } else {
+            slice.iter().map(|&b| u64::from(b)).sum()
+        }
+    };
+
+    // Warm one pass (page-in), then time.
+    let mut sink = 0u64;
+    for &i in &order {
+        sink = sink.wrapping_add(touch(&raw[i * frame_bytes..(i + 1) * frame_bytes]));
+    }
+    black_box(sink);
+
+    let t0 = Instant::now();
+    let mut sink = 0u64;
+    for _ in 0..passes {
+        for &i in &order {
+            sink = sink.wrapping_add(touch(&raw[i * frame_bytes..(i + 1) * frame_bytes]));
+        }
+    }
+    black_box(sink);
+    let elapsed = t0.elapsed().as_secs_f64();
+
+    let total = (n * passes) as f64;
+    let mode = if copy {
+        "materialized copy"
+    } else {
+        "zero-copy view"
+    };
+    println!("clawhdf5 ({mode}): {n} frames x {passes} passes in {elapsed:.3}s");
+    println!("clawhdf5 ({mode}): {:.0} samples/sec", total / elapsed);
+}
+
+fn shuffled(n: usize) -> Vec<usize> {
+    let mut v: Vec<usize> = (0..n).collect();
+    let mut state: u64 = 0x9E37_79B9_7F4A_7C15;
+    for i in (1..n).rev() {
+        state = state
+            .wrapping_mul(6364136223846793005)
+            .wrapping_add(1442695040888963407);
+        let j = (state >> 33) as usize % (i + 1);
+        v.swap(i, j);
+    }
+    v
+}
@@ -4,11 +4,39 @@
 //! Since no embedding model is available at bench time, all embeddings are zero vectors
 //! and `hybrid_search` operates in BM25-only mode (vector_weight=0.0, keyword_weight=1.0).
 //!
-//! This matches the MemX paper methodology: evaluate retrieval recall, not answer generation.
+//! # Scoring target (read before citing any number from this harness)
+//!
+//! - **Metric: retrieval recall.** A "hit" means the gold-labelled memory appeared in
+//!   the top-k. No answer is generated and none is scored — the dataset's `answer`
+//!   field is deserialized and deliberately never read. This is **not** the official
+//!   LongMemEval metric, which is end-to-end QA accuracy (retrieve → generate → LLM
+//!   judge). Reporting retrieval recall as QA accuracy overstates by 20–30 points.
+//! - **Dataset: whichever variant you point it at.** Both `longmemeval_oracle`
+//!   (evidence sessions only — a substantially easier corpus) and the full
+//!   `longmemeval_s` haystack are supported. The harness does not trust the
+//!   filename: [`DatasetProfile`] measures evidence-session density from the
+//!   data and labels the run from that, so a mislabelled input cannot produce a
+//!   mislabelled result.
+//! - **Session-level metrics are degenerate when evidence density is high**, and
+//!   the report says so per run rather than assuming it. On the oracle variant
+//!   the haystack is essentially all-evidence, so any returned document is a
+//!   session-level hit at rank 0 by construction; only turn-level
+//!   (`has_answer == true` on the source turn) measures the retriever there. On
+//!   the full haystack, session-level recall is meaningful.
+//! - **Not comparable to MemX's Hit@5=51.6% / MRR=0.380**, which is *fact-level*
+//!   granularity over 220,349 records from 19,195 sessions.
+//!
+//! See `BENCHMARKS.md` § "Retracted: session-level recall and the MemX comparison".
 //!
 //! # Usage
 //! ```
-//! cargo run --release --bin longmemeval_bench [path/to/longmemeval_oracle.json]
+//! cargo run --release --bin longmemeval_bench [PATH] [--limit N]
+//!
+//! # Usage: full haystack
+//! ```
+//! cargo run --release --bin longmemeval_bench -- \
+//!     benchmarks/longmemeval/longmemeval_s_cleaned.json --limit 50
+//! ```
 //! ```
 //!
 //! # WASM Note
@@ -21,12 +49,80 @@
 use std::collections::{HashMap, HashSet};
 use std::time::{Duration, Instant};

+// `#[path]` keeps the module beside its binary without Cargo autodiscovering it
+// as a second bin target (which a bare `src/bin/embedder.rs` would be).
+#[cfg(feature = "embeddings")]
+#[path = "longmemeval_bench/embedder.rs"]
+mod embedder;
+
 use clawhdf5_agent::{AgentMemory, HDF5Memory, MemoryConfig, MemoryEntry};
 use serde::Deserialize;
 use tempfile::TempDir;

 const EMBEDDING_DIM: usize = 384;

+/// A retrieval configuration: how much of the score comes from each stage.
+#[derive(Clone, Copy)]
+struct Mode {
+    label: &'static str,
+    vector_weight: f32,
+    keyword_weight: f32,
+}
+
+/// The only mode available without real embeddings. Passing zero vectors with
+/// `vector_weight = 0.0` is what made the vector stage inert.
+const BM25_ONLY: Mode = Mode {
+    label: "BM25 only (vector stage inert)",
+    vector_weight: 0.0,
+    keyword_weight: 1.0,
+};
+#[cfg(feature = "embeddings")]
+const VECTOR_ONLY: Mode = Mode {
+    label: "Vector only (MiniLM + HNSW)",
+    vector_weight: 1.0,
+    keyword_weight: 0.0,
+};
+/// Tuned by `--sweep` over the full haystack. The former 0.7/0.3 was a
+/// documented default that had never been searched, and the sweep found it
+/// strictly dominated: 0.4/0.6 is better on Hit@1, Hit@5, Hit@10 and MRR at
+/// both granularities.
+#[cfg(feature = "embeddings")]
+const HYBRID: Mode = Mode {
+    label: "Hybrid (0.4 vector / 0.6 BM25, tuned)",
+    vector_weight: 0.4,
+    keyword_weight: 0.6,
+};
+
+/// Every 0.1 step of vector weight, keyword weight taking the remainder.
+///
+/// Labels are leaked to `&'static str` because `Mode::label` is a `&'static
+/// str` for the eleven named modes and a sweep is a short-lived process; the
+/// alternative is threading a lifetime through the whole report path for a
+/// diagnostic mode.
+#[cfg(feature = "embeddings")]
+fn sweep_modes() -> Vec<Mode> {
+    (0..=10)
+        .map(|i| {
+            let v = i as f32 / 10.0;
+            Mode {
+                label: Box::leak(format!("sweep v={v:.1} / k={:.1}", 1.0 - v).into_boxed_str()),
+                vector_weight: v,
+                keyword_weight: 1.0 - v,
+            }
+        })
+        .collect()
+}
+
+/// Text -> embedding, built once for the whole corpus.
+type EmbeddingMap = HashMap<String, Vec<f32>>;
+
+/// Look up a real embedding, falling back to zeros when running BM25-only.
+fn embedding_for(map: Option<&EmbeddingMap>, text: &str) -> Vec<f32> {
+    map.and_then(|m| m.get(text))
+        .cloned()
+        .unwrap_or_else(|| vec![0.0f32; EMBEDDING_DIM])
+}
+
 // ---------------------------------------------------------------------------
 // JSON data types
 // ---------------------------------------------------------------------------
@@ -168,7 +264,12 @@ struct EvalResult {
    latency: Duration,
 }

-fn evaluate_question(q: &Question, top_k: usize) -> EvalResult {
+fn evaluate_question(
+    q: &Question,
+    top_k: usize,
+    mode: Mode,
+    embeddings: Option<&EmbeddingMap>,
+) -> EvalResult {
    let dir = TempDir::new().expect("failed to create temp dir");
    let mut config = MemoryConfig::new(dir.path().join("lme.h5"), "lme-bench", EMBEDDING_DIM);
    config.wal_enabled = false;
@@ -190,7 +291,7 @@ fn evaluate_question(q: &Question, top_k: usize) -> EvalResult {
        for turn in session {
            entries.push(MemoryEntry {
                chunk: turn.content.clone(),
-                embedding: vec![0.0f32; EMBEDDING_DIM],
+                embedding: embedding_for(embeddings, &turn.content),
                source_channel: "longmemeval".to_string(),
                timestamp: ts,
                session_id: sess_id.to_string(),
@@ -218,10 +319,15 @@ fn evaluate_question(q: &Question, top_k: usize) -> EvalResult {
    // Set of session IDs that contain the answer
    let answer_sess_set: HashSet<&str> = q.answer_session_ids.iter().map(String::as_str).collect();

-    // Run hybrid search (BM25-only: vector_weight=0.0, keyword_weight=1.0)
-    let zero_emb = vec![0.0f32; EMBEDDING_DIM];
+    let query_emb = embedding_for(embeddings, &q.question);
    let t0 = Instant::now();
-    let results = memory.hybrid_search(&zero_emb, &q.question, 0.0, 1.0, top_k);
+    let results = memory.hybrid_search(
+        &query_emb,
+        &q.question,
+        mode.vector_weight,
+        mode.keyword_weight,
+        top_k,
+    );
    let latency = t0.elapsed();

    // Session-level recall
@@ -286,17 +392,133 @@ fn evaluate_question(q: &Question, top_k: usize) -> EvalResult {
 // Report printing
 // ---------------------------------------------------------------------------

-fn print_report(overall: &Metrics, by_type: &HashMap<String, Metrics>) {
+// ---------------------------------------------------------------------------
+// Dataset profile — measured, not assumed
+// ---------------------------------------------------------------------------
+
+/// Shape of the loaded corpus, computed from the data itself.
+///
+/// The variant used to be a hardcoded `"oracle"` string in the report and the
+/// JSON summary, so pointing the harness at `longmemeval_s` would have produced
+/// full-haystack numbers labelled oracle. Everything here is derived from the
+/// questions instead, which means the label cannot drift from the corpus and a
+/// mislabelled input file cannot produce a mislabelled result.
+struct DatasetProfile {
+    n_questions: usize,
+    mean_sessions: f64,
+    mean_turns: f64,
+    /// Mean over questions of `|answer_sessions| / |haystack_sessions|`.
+    ///
+    /// This is what actually decides whether session-level recall means
+    /// anything. At ~1.0 every haystack session is an evidence session, so any
+    /// returned document is a session-level hit by construction.
+    evidence_density: f64,
+}
+
+impl DatasetProfile {
+    fn measure(questions: &[Question]) -> Self {
+        let n = questions.len().max(1) as f64;
+        let mut sessions = 0.0;
+        let mut turns = 0.0;
+        let mut density = 0.0;
+        for q in questions {
+            let n_sess = q.haystack_sessions.len();
+            sessions += n_sess as f64;
+            turns += q.haystack_sessions.iter().map(Vec::len).sum::<usize>() as f64;
+            if n_sess > 0 {
+                let evidence: HashSet<&str> =
+                    q.answer_session_ids.iter().map(String::as_str).collect();
+                let hit = q
+                    .haystack_session_ids
+                    .iter()
+                    .filter(|id| evidence.contains(id.as_str()))
+                    .count();
+                density += hit as f64 / n_sess as f64;
+            }
+        }
+        Self {
+            n_questions: questions.len(),
+            mean_sessions: sessions / n,
+            mean_turns: turns / n,
+            evidence_density: density / n,
+        }
+    }
+
+    /// Above this share of evidence sessions, session-level recall is measuring
+    /// the corpus shape rather than the retriever.
+    const DEGENERACY_THRESHOLD: f64 = 0.9;
+
+    const fn session_level_degenerate(&self) -> bool {
+        self.evidence_density > Self::DEGENERACY_THRESHOLD
+    }
+
+    /// Variant name inferred from evidence density, not from the filename.
+    const fn variant(&self) -> &'static str {
+        if self.session_level_degenerate() {
+            "oracle"
+        } else {
+            "full_haystack"
+        }
+    }
+}
+
+fn print_report(
+    overall: &Metrics,
+    by_type: &HashMap<String, Metrics>,
+    profile: &DatasetProfile,
+    mode: Mode,
+) {
    println!("=================================================================");
-    println!("  LongMemEval Benchmark  (BM25-only retrieval, zero embeddings)");
+    println!("  LongMemEval Benchmark  —  {}", mode.label);
    println!("=================================================================");
    println!();
-    println!("Mode: vector_weight=0.0 / keyword_weight=1.0 (pure BM25)");
-    println!("Note: MemX (arxiv:2603.16171) with full system: Hit@5=51.6%, MRR=0.380");
-    println!("      BM25-only numbers are expected to be lower — honest baseline.");
+    println!(
+        "Mode: vector_weight={:.1} / keyword_weight={:.1}",
+        mode.vector_weight, mode.keyword_weight
+    );
+    println!();
+    println!("Scoring target: RETRIEVAL RECALL (did the gold memory land in top-k).");
+    println!("  No answer is generated or scored. This is NOT the official");
+    println!("  LongMemEval metric (QA accuracy via retrieve+generate+judge).");
+    println!(
+        "Dataset: {} — {} questions, {:.1} sessions and {:.0} turns per question,",
+        profile.variant(),
+        profile.n_questions,
+        profile.mean_sessions,
+        profile.mean_turns,
+    );
+    println!(
+        "  {:.1}% of haystack sessions are evidence sessions.",
+        profile.evidence_density * 100.0
+    );
+    if profile.session_level_degenerate() {
+        println!("  This is the evidence-only corpus, NOT the full longmemeval_s");
+        println!("  haystack — a substantially easier retrieval problem.");
+    } else {
+        println!("  This is a full-haystack corpus: evidence sessions are a small");
+        println!("  minority, so retrieval has to actually discriminate.");
+    }
+    println!();
+    println!("Do NOT compare these to MemX's Hit@5=51.6% / MRR=0.380: that is");
+    println!("  fact-level granularity over 220,349 records from 19,195 sessions.");
+    println!("  Different granularity and a corpus larger by orders of magnitude.");
    println!();

    println!("## Session-Level Recall  (n={})", overall.count);
+    if profile.session_level_degenerate() {
+        println!(
+            "  [DEGENERATE — {:.1}% of haystack sessions are evidence sessions, so a",
+            profile.evidence_density * 100.0
+        );
+        println!("   returned document is a session-level hit almost by construction.");
+        println!("   This measures the corpus shape, not the retriever. Use turn-level.]");
+    } else {
+        println!(
+            "  [Meaningful on this corpus — only {:.1}% of haystack sessions are",
+            profile.evidence_density * 100.0
+        );
+        println!("   evidence sessions, so a hit reflects the retriever's discrimination.]");
+    }
    println!(
        "  Hit@1:  {:5.1}%   Hit@5:  {:5.1}%   Hit@10: {:5.1}%   MRR: {:.4}",
        overall.hit1_session_pct(),
@@ -380,7 +602,26 @@ fn print_report(overall: &Metrics, by_type: &HashMap<String, Metrics>) {
    println!("```json");
    println!("{{");
    println!("  \"benchmark\": \"longmemeval\",");
-    println!("  \"mode\": \"bm25_only\",");
+    println!(
+        "  \"mode\": \"vector_{:.1}_keyword_{:.1}\",",
+        mode.vector_weight, mode.keyword_weight
+    );
+    println!("  \"dataset_variant\": \"{}\",", profile.variant());
+    println!("  \"scoring_target\": \"retrieval_recall\",");
+    println!("  \"k\": 10,");
+    println!(
+        "  \"session_level_degenerate\": {},",
+        profile.session_level_degenerate()
+    );
+    println!(
+        "  \"evidence_session_density\": {:.4},",
+        profile.evidence_density
+    );
+    println!(
+        "  \"mean_sessions_per_question\": {:.2},",
+        profile.mean_sessions
+    );
+    println!("  \"mean_turns_per_question\": {:.1},", profile.mean_turns);
    println!(
        "  \"total_questions\": {},",
        overall.count + overall.abstention_total
@@ -403,10 +644,16 @@ fn print_report(overall: &Metrics, by_type: &HashMap<String, Metrics>) {
        overall.mrr_turn()
    );
    println!("  }},");
-    println!(
-        "  \"abstention_accuracy\": {:.4},",
-        overall.abstention_pct() / 100.0
-    );
+    // `null`, not 0.0 — a corpus with no abstention questions has no abstention
+    // accuracy, and emitting 0.0 reads as total failure at a task never posed.
+    if overall.abstention_total > 0 {
+        println!(
+            "  \"abstention_accuracy\": {:.4},",
+            overall.abstention_pct() / 100.0
+        );
+    } else {
+        println!("  \"abstention_accuracy\": null,");
+    }
    println!("  \"latency_us\": {{");
    println!(
        "    \"avg\": {:.1}, \"p50\": {:.1}, \"p95\": {:.1}, \"p99\": {:.1}",
@@ -425,17 +672,152 @@ fn print_report(overall: &Metrics, by_type: &HashMap<String, Metrics>) {
 // ---------------------------------------------------------------------------

 fn main() {
-    let json_path = std::env::args()
-        .nth(1)
-        .unwrap_or_else(|| "benchmarks/longmemeval/longmemeval_oracle.json".to_string());
+    let mut json_path: Option<String> = None;
+    let mut limit: Option<usize> = None;
+    let mut weights_dir: Option<String> = None;
+    let mut sweep = false;
+    let mut args = std::env::args().skip(1);
+    while let Some(arg) = args.next() {
+        match arg.as_str() {
+            "--limit" => {
+                let v = args.next().expect("--limit needs a value");
+                limit = Some(v.parse().expect("--limit must be a positive integer"));
+            }
+            "--sweep" => sweep = true,
+            "--embeddings" => {
+                weights_dir = Some(args.next().expect("--embeddings needs a directory"));
+            }
+            "--help" | "-h" => {
+                eprintln!(
+                    "usage: longmemeval_bench [PATH] [--limit N]\n\n\
+                     PATH     dataset JSON; defaults to the oracle variant.\n\
+                              longmemeval_s works too — the harness measures which\n\
+                              variant it was given rather than trusting the filename.\n\
+                     --limit  evaluate N questions, sampled evenly across the file\n\
+                              rather than as a prefix — the dataset is ordered by\n\
+                              question type, so a prefix samples one type only.\n\
+                     --embeddings DIR\n\
+                              directory holding all-MiniLM-L6-v2's model.safetensors\n\
+                              and tokenizer.json. Enables the vector stage and reports\n\
+                              BM25-only, vector-only, and hybrid separately. Requires\n\
+                              --features embeddings; without it the vector stage is\n\
+                              inert and only the BM25 row is produced.\n\
+                     --sweep  instead of the three named modes, sweep vector_weight\n\
+                              from 0.0 to 1.0 in 0.1 steps. The 0.7/0.3 default was\n\
+                              never searched; this is what searches it."
+                );
+                return;
+            }
+            other => json_path = Some(other.to_string()),
+        }
+    }
+    let json_path =
+        json_path.unwrap_or_else(|| "benchmarks/longmemeval/longmemeval_oracle.json".to_string());

    eprintln!("Loading: {json_path}");
    let data = std::fs::read_to_string(&json_path)
        .unwrap_or_else(|e| panic!("Failed to read {json_path}: {e}"));
-    let questions: Vec<Question> = serde_json::from_str(&data).expect("Failed to parse JSON");
+    let mut questions: Vec<Question> = serde_json::from_str(&data).expect("Failed to parse JSON");
+    if let Some(n) = limit
+        && n < questions.len()
+    {
+        // Stride rather than truncate. The dataset is ordered by question type,
+        // so taking a prefix samples one type: `--limit 20` on longmemeval_s
+        // returns 20 `single-session-user` questions and nothing else, which
+        // reads as a whole-dataset result but is not one.
+        let total = questions.len();
+        let step = total as f64 / n as f64;
+        let keep: HashSet<usize> = (0..n)
+            .map(|i| ((i as f64 * step) as usize).min(total - 1))
+            .collect();
+        questions = questions
+            .into_iter()
+            .enumerate()
+            .filter(|(i, _)| keep.contains(i))
+            .map(|(_, q)| q)
+            .collect();
+        eprintln!(
+            "Sampling {} of {total} questions, evenly strided (--limit)",
+            questions.len()
+        );
+    }
    let total = questions.len();
    eprintln!("Loaded {total} questions");

+    let profile = DatasetProfile::measure(&questions);
+    eprintln!(
+        "Corpus: {} variant — {:.1} sessions / {:.0} turns per question, \
+         {:.1}% evidence-session density",
+        profile.variant(),
+        profile.mean_sessions,
+        profile.mean_turns,
+        profile.evidence_density * 100.0,
+    );
+
+    // Build the embedding table once for the whole corpus, if asked for.
+    let embeddings: Option<EmbeddingMap> = weights_dir
+        .as_deref()
+        .map(|dir| load_embeddings(dir, &questions));
+    if embeddings.is_none() && weights_dir.is_some() {
+        eprintln!("warning: --embeddings ignored (build with --features embeddings)");
+    }
+
+    let modes: Vec<Mode> = if embeddings.is_some() {
+        #[cfg(feature = "embeddings")]
+        {
+            if sweep {
+                sweep_modes()
+            } else {
+                vec![BM25_ONLY, VECTOR_ONLY, HYBRID]
+            }
+        }
+        #[cfg(not(feature = "embeddings"))]
+        {
+            vec![BM25_ONLY]
+        }
+    } else {
+        if sweep {
+            eprintln!("warning: --sweep needs --embeddings; running BM25 only");
+        }
+        vec![BM25_ONLY]
+    };
+
+    for (mode_idx, mode) in modes.iter().enumerate() {
+        eprintln!("[{}/{}] {}", mode_idx + 1, modes.len(), mode.label);
+        run_mode(&questions, *mode, embeddings.as_ref(), &profile);
+    }
+}
+
+/// Load and encode the corpus. Returns `None` unless the `embeddings` feature
+/// is compiled in, so the flag degrades to a warning rather than a hard error.
+#[cfg(feature = "embeddings")]
+fn load_embeddings(dir: &str, questions: &[Question]) -> EmbeddingMap {
+    let enc = embedder::Embedder::load(std::path::Path::new(dir))
+        .unwrap_or_else(|e| panic!("failed to load embedder from {dir}: {e}"));
+    let texts = questions.iter().flat_map(|q| {
+        q.haystack_sessions
+            .iter()
+            .flatten()
+            .map(|t| t.content.clone())
+            .chain(std::iter::once(q.question.clone()))
+    });
+    enc.encode_unique(texts)
+        .unwrap_or_else(|e| panic!("embedding failed: {e}"))
+}
+
+#[cfg(not(feature = "embeddings"))]
+fn load_embeddings(_dir: &str, _questions: &[Question]) -> EmbeddingMap {
+    EmbeddingMap::new()
+}
+
+/// Evaluate every question under one retrieval mode and print its report.
+fn run_mode(
+    questions: &[Question],
+    mode: Mode,
+    embeddings: Option<&EmbeddingMap>,
+    profile: &DatasetProfile,
+) {
+    let total = questions.len();
    let mut overall = Metrics::default();
    let mut by_type: HashMap<String, Metrics> = HashMap::new();

@@ -444,7 +826,7 @@ fn main() {
            eprint!("\r  [{}/{}] evaluating...", i + 1, total);
        }

-        let result = evaluate_question(q, 10);
+        let result = evaluate_question(q, 10, mode, embeddings);

        let is_abs = q.question_type.ends_with("_abs");
        let base_type = if is_abs {
@@ -509,5 +891,5 @@ fn main() {

    eprintln!("\r  [{total}/{total}] done.          ");
    eprintln!();
-    print_report(&overall, &by_type);
+    print_report(&overall, &by_type, profile, mode);
 }
@@ -0,0 +1,170 @@
+//! Optional MiniLM sentence embedder for the LongMemEval bench.
+//!
+//! Compiled only under the `embeddings` feature, so the default build of a
+//! project that prides itself on having no heavyweight dependencies stays
+//! exactly as it was. Without it the bench runs BM25-only, as it always has.
+//!
+//! Loads `sentence-transformers/all-MiniLM-L6-v2` — the same checkpoint
+//! omni-cortex uses — and produces 384-d mean-pooled, L2-normalised sentence
+//! embeddings, which is the published recipe for this model (mean over token
+//! states weighted by the attention mask, *not* the `[CLS]` pooler output).
+
+use std::collections::HashMap;
+use std::path::Path;
+
+use candle_core::{DType, Device, Tensor};
+use candle_nn::VarBuilder;
+use candle_transformers::models::bert::{BertModel, Config, HiddenAct};
+use tokenizers::Tokenizer;
+
+/// Sequences encoded per forward pass. Larger batches amortise the transformer
+/// call; 64 keeps peak memory modest while still saturating a CPU.
+const BATCH: usize = 64;
+
+/// A loaded MiniLM encoder.
+pub struct Embedder {
+    model: BertModel,
+    tokenizer: Tokenizer,
+    device: Device,
+}
+
+impl Embedder {
+    /// Load from a directory holding `model.safetensors` and `tokenizer.json`.
+    ///
+    /// `config.json` is read when present; otherwise the published MiniLM-L6-v2
+    /// architecture constants are used, which are pinned rather than guessed.
+    pub fn load(dir: &Path) -> Result<Self, Box<dyn std::error::Error>> {
+        // CUDA when the feature is on and a device is actually present; the CPU
+        // path is correct but roughly two orders of magnitude slower, which is
+        // the difference between minutes and most of a day on the full haystack.
+        let device = match Device::new_cuda(0) {
+            Ok(d) => {
+                eprintln!("Embedder: CUDA device 0");
+                d
+            }
+            Err(e) => {
+                // Loud, because the CPU path is correct but ~100x slower: the
+                // full longmemeval_s haystack is minutes on a GPU and most of a
+                // day on 8 cores. Silently falling back looks like a hang.
+                eprintln!("Embedder: CPU — CUDA unavailable ({e})");
+                eprintln!(
+                    "  WARNING: CPU embedding is roughly two orders of magnitude slower.\n                       Expect minutes for longmemeval_oracle and many hours for the full\n                       longmemeval_s haystack. For the GPU path, rebuild with\n                       `--features embeddings-cuda` and make sure `nvcc` is on PATH\n                       (it ships in /usr/local/cuda/bin, which is often not exported)."
+                );
+                Device::Cpu
+            }
+        };
+        let weights = dir.join("model.safetensors");
+        let tok_path = dir.join("tokenizer.json");
+
+        let config: Config = match std::fs::read_to_string(dir.join("config.json")) {
+            Ok(raw) => serde_json::from_str(&raw)?,
+            Err(_) => Config {
+                vocab_size: 30_522,
+                hidden_size: 384,
+                num_hidden_layers: 6,
+                num_attention_heads: 12,
+                intermediate_size: 1_536,
+                hidden_act: HiddenAct::Gelu,
+                hidden_dropout_prob: 0.0,
+                max_position_embeddings: 512,
+                type_vocab_size: 2,
+                initializer_range: 0.02,
+                layer_norm_eps: 1e-12,
+                pad_token_id: 0,
+                position_embedding_type: Default::default(),
+                use_cache: false,
+                classifier_dropout: None,
+                model_type: None,
+            },
+        };
+
+        let vb = unsafe { VarBuilder::from_mmaped_safetensors(&[weights], DType::F32, &device)? };
+        let model = BertModel::load(vb, &config)?;
+        let tokenizer = Tokenizer::from_file(&tok_path).map_err(|e| e.to_string())?;
+
+        Ok(Self {
+            model,
+            tokenizer,
+            device,
+        })
+    }
+
+    /// Encode `texts` into 384-d unit vectors, in order.
+    fn encode_batch(&self, texts: &[&str]) -> Result<Vec<Vec<f32>>, Box<dyn std::error::Error>> {
+        let mut tk = self.tokenizer.clone();
+        let tk = tk
+            .with_padding(Some(tokenizers::PaddingParams::default()))
+            .with_truncation(Some(tokenizers::TruncationParams {
+                max_length: 512,
+                ..Default::default()
+            }))
+            .map_err(|e| e.to_string())?;
+        let encodings = tk
+            .encode_batch(texts.to_vec(), true)
+            .map_err(|e| e.to_string())?;
+
+        let ids: Vec<u32> = encodings
+            .iter()
+            .flat_map(|e| e.get_ids().to_vec())
+            .collect();
+        let mask: Vec<u32> = encodings
+            .iter()
+            .flat_map(|e| e.get_attention_mask().to_vec())
+            .collect();
+        let (b, l) = (encodings.len(), encodings[0].get_ids().len());
+
+        let ids = Tensor::from_vec(ids, (b, l), &self.device)?;
+        let mask = Tensor::from_vec(mask, (b, l), &self.device)?;
+        let type_ids = ids.zeros_like()?;
+
+        let hidden = self.model.forward(&ids, &type_ids, Some(&mask))?;
+
+        // Mean-pool over real tokens only: sum(hidden * mask) / sum(mask).
+        let mask_f = mask.to_dtype(DType::F32)?.unsqueeze(2)?;
+        let summed = hidden.broadcast_mul(&mask_f)?.sum(1)?;
+        let counts = mask_f.sum(1)?.clamp(1e-9, f32::INFINITY)?;
+        let pooled = summed.broadcast_div(&counts)?;
+
+        // L2-normalise so cosine similarity is a plain dot product.
+        let norm = pooled
+            .sqr()?
+            .sum_keepdim(1)?
+            .sqrt()?
+            .clamp(1e-12, f32::INFINITY)?;
+        let normed = pooled.broadcast_div(&norm)?;
+
+        Ok(normed.to_vec2::<f32>()?)
+    }
+
+    /// Encode every distinct string in `texts` once, returning a lookup map.
+    ///
+    /// LongMemEval's haystack sessions are drawn from a shared pool, so the same
+    /// turn text recurs across many questions. Deduplicating before encoding is
+    /// the difference between encoding the corpus once and encoding it per
+    /// question.
+    pub fn encode_unique(
+        &self,
+        texts: impl IntoIterator<Item = String>,
+    ) -> Result<HashMap<String, Vec<f32>>, Box<dyn std::error::Error>> {
+        let mut unique: Vec<String> = texts.into_iter().collect();
+        unique.sort_unstable();
+        unique.dedup();
+
+        let total = unique.len();
+        eprintln!("Embedding {total} unique texts with MiniLM (batch {BATCH})...");
+
+        let mut out = HashMap::with_capacity(total);
+        for (n, chunk) in unique.chunks(BATCH).enumerate() {
+            let refs: Vec<&str> = chunk.iter().map(String::as_str).collect();
+            let vecs = self.encode_batch(&refs)?;
+            for (text, v) in chunk.iter().zip(vecs) {
+                out.insert(text.clone(), v);
+            }
+            if n % 50 == 0 {
+                eprint!("\r  [{}/{}] embedded...", (n * BATCH).min(total), total);
+            }
+        }
+        eprintln!("\r  [{total}/{total}] embedded.          ");
+        Ok(out)
+    }
+}
@@ -17,4 +17,4 @@ path = "src/main.rs"
 clawhdf5-agent = { path = "../clawhdf5-agent", version = "2.1.0" }
 clap = { version = "4", features = ["derive", "env"] }
 serde_json = "1"
-serde = { version = "1", features = ["derive"] }
+serde = { workspace = true }
@@ -2,7 +2,7 @@
 name = "clawhdf5-filters"
 version = "2.1.0"
 edition = "2024"
-description = "Filter and compression pipeline for rustyhdf5"
+description = "Filter and compression pipeline for clawhdf5"
 license = "MIT"
 repository = "https://github.com/redclawsystems/clawhdf5"
 readme = "README.md"
@@ -14,7 +14,7 @@ flate2 = { version = "1", default-features = false, features = ["rust_backend"]
 miniz_oxide = "0.8"

 [dev-dependencies]
-criterion = { version = "0.5", features = ["html_reports"] }
+criterion = { workspace = true }

 [[bench]]
 name = "deflate_bench"
@@ -270,14 +270,29 @@ pub(crate) fn flate2_decompress_preallocated(
    Ok(output)
 }

+/// Absolute ceiling on decompressed output when the caller has no size hint,
+/// preventing unbounded allocation from a hostile/corrupted zlib stream.
+const MAX_DECOMPRESS_SIZE: usize = 256 * 1024 * 1024;
+
 /// Streaming decompress with dynamic sizing (when output size is unknown).
+///
+/// Bounded by [`MAX_DECOMPRESS_SIZE`] since there is no chunk-size hint to
+/// validate against here — an unbounded `read_to_end` would let a hostile
+/// zlib stream force arbitrarily large allocation (a "zlib bomb").
 pub(crate) fn flate2_decompress_streaming(data: &[u8]) -> Result<Vec<u8>, String> {
    use std::io::Read;
-    let mut decoder = flate2::read::ZlibDecoder::new(data);
+    let decoder = flate2::read::ZlibDecoder::new(data);
    let mut result = Vec::new();
    decoder
+        .take(MAX_DECOMPRESS_SIZE as u64 + 1)
        .read_to_end(&mut result)
        .map_err(|e| e.to_string())?;
+    if result.len() > MAX_DECOMPRESS_SIZE {
+        return Err(format!(
+            "decompressed output exceeds {} MiB limit",
+            MAX_DECOMPRESS_SIZE / 1024 / 1024
+        ));
+    }
    Ok(result)
 }

@@ -11,6 +11,7 @@ categories = ["parser-implementations", "science", "encoding", "no-std"]

 [dependencies]
 byteorder = { version = "1", default-features = false }
+portable-atomic = { version = "1" }
 flate2 = { version = "1", default-features = false, features = ["rust_backend"], optional = true }
 sha2 = { version = "0.10", default-features = false, optional = true }
 rayon = { version = "1", optional = true }
@@ -23,7 +24,7 @@ pco = { version = "1.0", optional = true }

 [dev-dependencies]
 serde_json = "1"
-criterion = { version = "0.5", features = ["html_reports"] }
+criterion = { workspace = true }
 clawhdf5-derive = { path = "../clawhdf5-derive", version = "2.1.0" }

 [[bench]]
@@ -31,7 +32,7 @@ name = "bench"
 harness = false

 [features]
-default = ["std", "checksum", "deflate", "provenance", "fast-deflate", "system-zlib-decompress"]
+default = ["std", "checksum", "deflate", "provenance", "system-zlib-decompress"]
 std = []
 checksum = []
 deflate = ["flate2"]
@@ -14,6 +14,9 @@ libfuzzer-sys = "0.4"
 path = ".."
 features = ["std", "checksum", "deflate"]

+[dependencies.clawhdf5]
+path = "../../clawhdf5"
+
 [workspace]
 members = ["."]

@@ -56,3 +59,8 @@ doc = false
 name = "fuzz_full_file"
 path = "fuzz_targets/fuzz_full_file.rs"
 doc = false
+
+[[bin]]
+name = "fuzz_dataset_read"
+path = "fuzz_targets/fuzz_dataset_read.rs"
+doc = false
@@ -1,4 +1,4 @@
-# Fuzz Testing for rustyhdf5-format
+# Fuzz Testing for clawhdf5-format

 Uses [cargo-fuzz](https://github.com/rust-fuzz/cargo-fuzz) (libFuzzer) to test parser robustness against malformed inputs.

@@ -21,13 +21,14 @@ rustup toolchain install nightly
 | `fuzz_btree_v2` | `BTreeV2Header::parse` | B-tree v2 header parsing |
 | `fuzz_filter_pipeline` | `FilterPipeline::parse` | Filter pipeline messages (v1/v2) |
 | `fuzz_full_file` | signature + superblock + root group | End-to-end file parsing chain |
+| `fuzz_dataset_read` | `Dataset::read_*` (via `clawhdf5`) | Walks every dataset in the parsed file and exercises the contiguous/chunked/compact raw-data read paths (`chunked_read.rs`, `data_read.rs`) that `fuzz_full_file` doesn't reach |

 ## Running

 Run a single target (runs indefinitely until stopped or a crash is found):

 ```bash
-cd crates/rustyhdf5-format
+cd crates/clawhdf5-format
 cargo +nightly fuzz run fuzz_datatype
 ```

@@ -41,12 +42,20 @@ Run all targets for 30 seconds each:

 ```bash
 for target in fuzz_superblock fuzz_object_header fuzz_datatype fuzz_dataspace \
-              fuzz_fractal_heap fuzz_btree_v2 fuzz_filter_pipeline fuzz_full_file; do
+              fuzz_fractal_heap fuzz_btree_v2 fuzz_filter_pipeline fuzz_full_file \
+              fuzz_dataset_read; do
    echo "=== $target ==="
    cargo +nightly fuzz run "$target" -- -max_total_time=30 -max_len=4096
 done
 ```

+## CI
+
+These targets are **not** run in CI (`.gitea/workflows/ci.yml`) — cargo-fuzz
+requires nightly and each meaningful run takes minutes, which doesn't fit a
+per-PR gate. Run them manually on a schedule (e.g. before a release, or after
+touching parser code) instead.
+
 ## Reproducing Crashes

 If a crash is found, the input is saved to `fuzz/artifacts/<target>/`. Reproduce with:
@@ -0,0 +1,45 @@
+#![no_main]
+use libfuzzer_sys::fuzz_target;
+
+const MAX_WALK_DEPTH: usize = 16;
+
+/// Walk groups/datasets from `group`, exercising every dataset-reading code
+/// path reachable through the public API (contiguous/chunked/compact raw
+/// reads via `chunked_read.rs`/`data_read.rs`). Depth-limited independently
+/// of any parser-level recursion guard, since this is fuzz-harness
+/// bookkeeping, not something under test.
+fn walk_group(group: &clawhdf5::Group, depth: usize) {
+    if depth > MAX_WALK_DEPTH {
+        return;
+    }
+    if let Ok(names) = group.datasets() {
+        for name in names {
+            if let Ok(dataset) = group.dataset(&name) {
+                let _ = dataset.shape();
+                let _ = dataset.max_dimensions();
+                let _ = dataset.dtype();
+                let _ = dataset.read_raw_ref();
+                let _ = dataset.read_f64();
+                let _ = dataset.read_f32();
+                let _ = dataset.read_i32();
+                let _ = dataset.read_i64();
+                let _ = dataset.read_u64();
+                let _ = dataset.read_string();
+            }
+        }
+    }
+    if let Ok(names) = group.groups() {
+        for name in names {
+            if let Ok(subgroup) = group.group(&name) {
+                walk_group(&subgroup, depth + 1);
+            }
+        }
+    }
+}
+
+fuzz_target!(|data: &[u8]| {
+    let Ok(file) = clawhdf5::File::from_bytes(data.to_vec()) else {
+        return;
+    };
+    walk_group(&file.root(), 0);
+});
@@ -24,6 +24,21 @@ pub struct BTreeV1Node {
    pub children: Vec<u64>,
 }

+/// Checks that `[offset, offset + needed)` fits within `data`, guarding the
+/// addition against `usize` overflow from a crafted near-`usize::MAX` offset.
+fn ensure_len(data: &[u8], offset: usize, needed: usize) -> Result<(), FormatError> {
+    if offset
+        .checked_add(needed)
+        .is_none_or(|end| end > data.len())
+    {
+        return Err(FormatError::UnexpectedEof {
+            expected: offset.saturating_add(needed),
+            available: data.len(),
+        });
+    }
+    Ok(())
+}
+
 fn read_offset(data: &[u8], pos: usize, size: u8) -> Result<u64, FormatError> {
    let s = size as usize;
    if pos.checked_add(s).is_none_or(|end| end > data.len()) {
@@ -45,7 +60,7 @@ fn read_offset(data: &[u8], pos: usize, size: u8) -> Result<u64, FormatError> {

 fn is_undefined(data: &[u8], pos: usize, size: u8) -> bool {
    let s = size as usize;
-    if pos + s > data.len() {
+    if ensure_len(data, pos, s).is_err() {
        return false;
    }
    data[pos..pos + s].iter().all(|&b| b == 0xFF)
@@ -65,12 +80,7 @@ impl BTreeV1Node {
        // + left_sibling(offset_size) + right_sibling(offset_size)
        let os = offset_size as usize;
        let header_size = 8 + os * 2;
-        if offset + header_size > file_data.len() {
-            return Err(FormatError::UnexpectedEof {
-                expected: offset + header_size,
-                available: file_data.len(),
-            });
-        }
+        ensure_len(file_data, offset, header_size)?;

        if &file_data[offset..offset + 4] != b"TREE" {
            return Err(FormatError::InvalidBTreeSignature);
@@ -99,12 +109,7 @@ impl BTreeV1Node {
        let eu = entries_used as usize;
        let key_size = os; // For type 0, key = offset_size
        let needed = eu * (key_size + os) + key_size; // eu children + (eu+1) keys
-        if pos + needed > file_data.len() {
-            return Err(FormatError::UnexpectedEof {
-                expected: pos + needed,
-                available: file_data.len(),
-            });
-        }
+        ensure_len(file_data, pos, needed)?;

        let mut keys = Vec::with_capacity(eu + 1);
        let mut children = Vec::with_capacity(eu);
@@ -241,6 +246,16 @@ mod tests {
        assert_eq!(node.right_sibling, None);
    }

+    #[test]
+    fn parse_near_usize_max_offset_rejected_without_overflow() {
+        let data = build_btree_node(0, 0, &[0, 5, 10], &[0x100, 0x200], None, None, 8);
+        let result = BTreeV1Node::parse(&data, usize::MAX - 4, 8, 8);
+        assert!(
+            matches!(result, Err(FormatError::UnexpectedEof { .. })),
+            "expected a clean UnexpectedEof, got {result:?}"
+        );
+    }
+
    #[test]
    fn parse_with_siblings_none() {
        let data = build_btree_node(0, 0, &[0, 8], &[0x300], None, None, 8);
@@ -16,6 +16,8 @@ use core::ops::{Deref, DerefMut};
 use alloc::collections::BTreeMap;
 #[cfg(feature = "std")]
 use std::collections::HashMap;
+#[cfg(feature = "std")]
+use std::sync::Arc;

 use crate::chunk_index::{ChunkIndex, ChunkLayout};
 use crate::chunked_read::ChunkInfo;
@@ -64,6 +66,11 @@ pub struct CacheAlignedBuffer {

 // SAFETY: The raw pointer is exclusively owned — no aliasing.
 unsafe impl Send for CacheAlignedBuffer {}
+// SAFETY: `CacheAlignedBuffer` exposes its contents only via `&[u8]`/`&mut
+// [u8]` through the ordinary borrow-checked `Deref`/`DerefMut` impls below —
+// the same access pattern as `Vec<u8>`, which is `Sync`. Needed so
+// `Arc<CacheAlignedBuffer>` (used by the chunk cache) is itself `Send`.
+unsafe impl Sync for CacheAlignedBuffer {}

 impl CacheAlignedBuffer {
    /// Allocate a new cache-line-aligned buffer of exactly `len` bytes,
@@ -223,7 +230,9 @@ pub const DEFAULT_MAX_SLOTS: usize = 521;
 #[cfg(feature = "std")]
 struct CachedChunk {
    coord: ChunkCoord,
-    data: CacheAlignedBuffer,
+    /// Shared so a cache hit is a refcount bump, not a copy of the whole
+    /// (potentially large) decompressed chunk.
+    data: Arc<CacheAlignedBuffer>,
    /// Monotonically increasing access counter for LRU ordering.
    last_access: u64,
 }
@@ -267,6 +276,12 @@ struct CacheInner {
    /// LRU cache of decompressed chunk data.
    slots: Vec<CachedChunk>,

+    /// Coordinate -> index into `slots`, for O(1) lookup instead of a linear
+    /// scan. Kept in sync with `slots` on every insert/evict/clear — in
+    /// particular, `slots.swap_remove(i)` moves the last element into slot
+    /// `i`, so the moved element's index entry must be updated too.
+    slot_index: HashMap<ChunkCoord, usize>,
+
    /// Current total bytes of cached decompressed data.
    current_bytes: usize,

@@ -344,6 +359,7 @@ impl ChunkCache {
                index: None,
                index_addr: None,
                slots: Vec::with_capacity(max_slots.min(64)),
+                slot_index: HashMap::with_capacity(max_slots.min(64)),
                current_bytes: 0,
                max_bytes,
                max_slots,
@@ -375,6 +391,7 @@ impl ChunkCache {
        inner.chunk_index = None;
        inner.chunk_layout = None;
        inner.slots.clear();
+        inner.slot_index.clear();
        inner.current_bytes = 0;
        inner.last_coord = None;
        inner.index_addr = Some(addr);
@@ -477,8 +494,20 @@ impl ChunkCache {

    /// Try to get cached decompressed data for a chunk coordinate.
    ///
-    /// Returns a clone of the cache-line-aligned buffer.
+    /// O(1) lookup. Returns an owned copy for API compatibility with callers
+    /// that need a `Vec<u8>`; prefer [`Self::get_decompressed_aligned`] when
+    /// an `Arc`-shared buffer works for the caller, since that avoids the
+    /// copy entirely.
    pub fn get_decompressed(&self, coord: &[u64]) -> Option<Vec<u8>> {
+        self.get_decompressed_aligned(coord)
+            .map(|arc| arc.as_slice().to_vec())
+    }
+
+    /// Try to get a reference-counted clone of the aligned buffer for a chunk.
+    ///
+    /// O(1) index lookup; the clone is an `Arc` refcount bump, not a copy of
+    /// the underlying decompressed data.
+    pub fn get_decompressed_aligned(&self, coord: &[u64]) -> Option<Arc<CacheAlignedBuffer>> {
        let mut inner = self.inner.lock().unwrap_or_else(|e| e.into_inner());
        inner.tick += 1;
        let tick = inner.tick;
@@ -500,36 +529,12 @@ impl ChunkCache {
        }
        inner.last_coord = Some(coord.to_vec());

-        let mut found = None;
-        for slot in inner.slots.iter_mut() {
-            if slot.coord.as_slice() == coord {
-                slot.last_access = tick;
-                found = Some(slot.data.to_vec());
-                break;
-            }
-        }
-        if let Some(ref data) = found {
-            inner.stats.hits += 1;
-            inner.stats.bytes_read += data.len() as u64;
+        let found = if let Some(&idx) = inner.slot_index.get(coord) {
+            inner.slots[idx].last_access = tick;
+            Some(Arc::clone(&inner.slots[idx].data))
        } else {
-            inner.stats.misses += 1;
-        }
-        found
-    }
-
-    /// Try to get a reference-counted clone of the aligned buffer for a chunk.
-    pub fn get_decompressed_aligned(&self, coord: &[u64]) -> Option<CacheAlignedBuffer> {
-        let mut inner = self.inner.lock().unwrap_or_else(|e| e.into_inner());
-        inner.tick += 1;
-        let tick = inner.tick;
-        let mut found = None;
-        for slot in inner.slots.iter_mut() {
-            if slot.coord.as_slice() == coord {
-                slot.last_access = tick;
-                found = Some(slot.data.clone());
-                break;
-            }
-        }
+            None
+        };
        if let Some(ref data) = found {
            inner.stats.hits += 1;
            inner.stats.bytes_read += data.len() as u64;
@@ -542,30 +547,39 @@ impl ChunkCache {
    /// Insert decompressed chunk data into the LRU cache.
    ///
    /// The data is stored in a [`CacheAlignedBuffer`] so subsequent reads
-    /// return cache-line-aligned memory.
-    pub fn put_decompressed(&self, coord: ChunkCoord, data: Vec<u8>) {
-        let aligned = CacheAlignedBuffer::from_slice(&data);
-        self.put_decompressed_aligned(coord, aligned);
+    /// return cache-line-aligned memory. Returns the `Arc`-shared buffer that
+    /// is now cached (or already was), so the caller can reuse it directly
+    /// instead of holding a separate copy of the same data.
+    pub fn put_decompressed(&self, coord: ChunkCoord, data: Vec<u8>) -> Arc<CacheAlignedBuffer> {
+        let aligned = CacheAlignedBuffer::from_vec(data);
+        self.put_decompressed_aligned(coord, aligned)
    }

    /// Insert an already-aligned buffer into the LRU cache.
-    pub fn put_decompressed_aligned(&self, coord: ChunkCoord, data: CacheAlignedBuffer) {
+    ///
+    /// Returns the `Arc`-shared buffer now held by the cache (the one just
+    /// inserted, or the existing cached copy if `coord` was already present).
+    pub fn put_decompressed_aligned(
+        &self,
+        coord: ChunkCoord,
+        data: CacheAlignedBuffer,
+    ) -> Arc<CacheAlignedBuffer> {
+        let data = Arc::new(data);
        let mut inner = self.inner.lock().unwrap_or_else(|e| e.into_inner());
        let data_len = data.len();

-        // Don't cache if single chunk exceeds budget
+        // Don't cache if single chunk exceeds budget — still return the data
+        // to the caller, just don't retain it.
        if data_len > inner.max_bytes {
-            return;
+            return data;
        }

        // Check if already present
        inner.tick += 1;
        let tick = inner.tick;
-        for slot in inner.slots.iter_mut() {
-            if slot.coord == coord {
-                slot.last_access = tick;
-                return; // already cached
-            }
+        if let Some(&idx) = inner.slot_index.get(&coord) {
+            inner.slots[idx].last_access = tick;
+            return Arc::clone(&inner.slots[idx].data); // already cached
        }

        // Evict until we have room
@@ -581,16 +595,26 @@ impl ChunkCache {
                .map(|(i, _)| i)
                .unwrap();
            let removed = inner.slots.swap_remove(lru_idx);
+            inner.slot_index.remove(&removed.coord);
+            // swap_remove moved the former last element into `lru_idx` (unless
+            // it *was* the last element) — fix up that element's index entry.
+            if lru_idx < inner.slots.len() {
+                let moved_coord = inner.slots[lru_idx].coord.clone();
+                inner.slot_index.insert(moved_coord, lru_idx);
+            }
            inner.current_bytes -= removed.data.len();
            inner.stats.evictions += 1;
        }

        inner.current_bytes += data_len;
+        let new_idx = inner.slots.len();
+        inner.slot_index.insert(coord.clone(), new_idx);
        inner.slots.push(CachedChunk {
            coord,
-            data,
+            data: Arc::clone(&data),
            last_access: tick,
        });
+        data
    }

    /// Clear the entire cache (index + decompressed data).
@@ -599,6 +623,7 @@ impl ChunkCache {
        inner.index = None;
        inner.index_addr = None;
        inner.slots.clear();
+        inner.slot_index.clear();
        inner.current_bytes = 0;
        inner.tick = 0;
        inner.last_coord = None;
@@ -607,11 +632,13 @@ impl ChunkCache {
        inner.chunk_layout = None;
    }

-    /// Hint that the given chunk coordinates will be accessed soon.
+    /// Record that the given chunk coordinates are predicted to be accessed
+    /// soon (bookkeeping only).
    ///
-    /// Pre-populates the chunk index for these coordinates so that
-    /// subsequent lookups are O(1). This does NOT pre-decompress the
-    /// chunks — it only ensures the index entries exist.
+    /// This does **not** prefetch or pre-decompress anything — it only
+    /// checks whether each coordinate is already in the chunk index and
+    /// updates access-pattern stats accordingly. Real prefetching (e.g.
+    /// background pre-decompression) is not implemented.
    pub fn prefetch_hint(&self, next_coords: &[ChunkCoord]) {
        let inner = self.inner.lock().unwrap_or_else(|e| e.into_inner());
        if inner.index.is_none() {
@@ -785,6 +812,50 @@ mod tests {
        assert_eq!(cache.cached_bytes(), 3);
    }

+    #[test]
+    fn slot_index_consistent_after_many_evictions() {
+        // Force repeated swap_remove evictions (small slot budget, many
+        // inserts) and confirm the coord -> slot index stays correct: every
+        // remaining coord must still resolve to its own data, not another
+        // slot's (which would happen if swap_remove's index fixup were wrong).
+        let cache = ChunkCache::with_capacity(1024 * 1024, 4); // max 4 slots
+
+        for i in 0..50u64 {
+            cache.put_decompressed(vec![i], vec![(i % 256) as u8; 8]);
+            // Interleave reads of a couple of earlier coords to churn LRU
+            // order (and thus which slot gets swap_remove'd) beyond simple
+            // FIFO eviction.
+            if i >= 2 {
+                let _ = cache.get_decompressed(&[i - 2]);
+            }
+        }
+
+        // Whatever remains in the cache (at most 4 slots) must return its
+        // own correct data.
+        for i in 0..50u64 {
+            if let Some(data) = cache.get_decompressed(&[i]) {
+                assert_eq!(
+                    data,
+                    vec![(i % 256) as u8; 8],
+                    "coord {i} returned wrong data after eviction churn"
+                );
+            }
+        }
+        assert!(cache.cached_chunk_count() <= 4);
+    }
+
+    #[test]
+    fn get_decompressed_aligned_shares_arc_on_hit() {
+        let cache = ChunkCache::new();
+        cache.put_decompressed(vec![0, 0], vec![9, 9, 9, 9]);
+        let a = cache.get_decompressed_aligned(&[0, 0]).unwrap();
+        let b = cache.get_decompressed_aligned(&[0, 0]).unwrap();
+        // A cache hit clones the Arc (refcount bump), not the underlying
+        // buffer — both handles point at the same allocation.
+        assert!(Arc::ptr_eq(&a, &b));
+        assert_eq!(a.as_slice(), &[9, 9, 9, 9]);
+    }
+
    // --- CacheAlignedBuffer tests ---

    #[test]
@@ -17,6 +17,8 @@ use crate::extensible_array::{ExtensibleArrayHeader, read_extensible_array_chunk
 use crate::filter_pipeline::FilterPipeline;
 use crate::filters::decompress_chunk;
 use crate::fixed_array::{FixedArrayHeader, read_fixed_array_chunks};
+#[cfg(feature = "std")]
+use std::sync::Arc;

 #[cfg(feature = "parallel")]
 use crate::parallel_read;
@@ -59,12 +61,7 @@ fn decompress_all_chunks(
    for chunk_info in chunks {
        let c_addr = chunk_info.address as usize;
        let size = chunk_info.chunk_size as usize;
-        if c_addr + size > file_data.len() {
-            return Err(FormatError::UnexpectedEof {
-                expected: c_addr + size,
-                available: file_data.len(),
-            });
-        }
+        ensure_len(file_data, c_addr, size)?;
        let raw_chunk = &file_data[c_addr..c_addr + size];

        let decompressed = if let Some(pl) = pipeline {
@@ -120,6 +117,21 @@ pub struct ChunkInfo {
    pub address: u64,
 }

+/// Checks that `[offset, offset + needed)` fits within `data`, guarding the
+/// addition against `usize` overflow from a crafted near-`usize::MAX` offset.
+fn ensure_len(data: &[u8], offset: usize, needed: usize) -> Result<(), FormatError> {
+    if offset
+        .checked_add(needed)
+        .is_none_or(|end| end > data.len())
+    {
+        return Err(FormatError::UnexpectedEof {
+            expected: offset.saturating_add(needed),
+            available: data.len(),
+        });
+    }
+    Ok(())
+}
+
 fn read_offset(data: &[u8], pos: usize, size: u8) -> Result<u64, FormatError> {
    let s = size as usize;
    if pos.checked_add(s).is_none_or(|end| end > data.len()) {
@@ -148,19 +160,33 @@ pub fn collect_chunk_info(
    btree_address: u64,
    ndims: usize,
    offset_size: u8,
-    _length_size: u8,
+    length_size: u8,
 ) -> Result<Vec<ChunkInfo>, FormatError> {
+    collect_chunk_info_inner(file_data, btree_address, ndims, offset_size, length_size, 0)
+}
+
+/// Maximum recursion depth for chunk B-tree traversal (malformed/cyclic data
+/// protection), matching `btree_v1.rs`'s `MAX_BTREE_DEPTH`.
+const MAX_CHUNK_BTREE_DEPTH: usize = 64;
+
+fn collect_chunk_info_inner(
+    file_data: &[u8],
+    btree_address: u64,
+    ndims: usize,
+    offset_size: u8,
+    _length_size: u8,
+    depth: usize,
+) -> Result<Vec<ChunkInfo>, FormatError> {
+    if depth > MAX_CHUNK_BTREE_DEPTH {
+        return Err(FormatError::NestingDepthExceeded);
+    }
+
    let offset = btree_address as usize;
    let os = offset_size as usize;

    // Parse B-tree v1 header
    let header_size = 8 + os * 2;
-    if offset + header_size > file_data.len() {
-        return Err(FormatError::UnexpectedEof {
-            expected: offset + header_size,
-            available: file_data.len(),
-        });
-    }
+    ensure_len(file_data, offset, header_size)?;

    if &file_data[offset..offset + 4] != b"TREE" {
        return Err(FormatError::InvalidBTreeSignature);
@@ -183,12 +209,7 @@ pub fn collect_chunk_info(
        // Leaf node: keys and children interleaved
        // key[0], child[0], key[1], child[1], ..., key[N-1], child[N-1], key[N]
        let needed = entries_used * (key_size + os) + key_size;
-        if pos + needed > file_data.len() {
-            return Err(FormatError::UnexpectedEof {
-                expected: pos + needed,
-                available: file_data.len(),
-            });
-        }
+        ensure_len(file_data, pos, needed)?;

        let mut chunks = Vec::with_capacity(entries_used);
        for _ in 0..entries_used {
@@ -229,12 +250,7 @@ pub fn collect_chunk_info(
    } else {
        // Internal node: recurse into children
        let needed = entries_used * (key_size + os) + key_size;
-        if pos + needed > file_data.len() {
-            return Err(FormatError::UnexpectedEof {
-                expected: pos + needed,
-                available: file_data.len(),
-            });
-        }
+        ensure_len(file_data, pos, needed)?;

        let mut child_addrs = Vec::with_capacity(entries_used);
        for _ in 0..entries_used {
@@ -246,8 +262,14 @@ pub fn collect_chunk_info(

        let mut all_chunks = Vec::new();
        for child_addr in child_addrs {
-            let child_chunks =
-                collect_chunk_info(file_data, child_addr, ndims, offset_size, _length_size)?;
+            let child_chunks = collect_chunk_info_inner(
+                file_data,
+                child_addr,
+                ndims,
+                offset_size,
+                _length_size,
+                depth + 1,
+            )?;
            all_chunks.extend(child_chunks);
        }
        Ok(all_chunks)
@@ -345,7 +367,9 @@ pub fn read_chunked_data(

    // Both v3 and v4 include element size as last dim (rank+1)
    let ndims = chunk_dimensions.len();
-    let rank = ndims - 1;
+    let rank = ndims
+        .checked_sub(1)
+        .ok_or_else(|| FormatError::ChunkedReadError("chunked layout has no dimensions".into()))?;
    let chunk_dims: Vec<usize> = chunk_dimensions[..rank]
        .iter()
        .map(|&d| d as usize)
@@ -384,24 +408,24 @@ pub fn read_chunked_data(
        }
        (4, Some(2)) => {
            // Implicit index — use spatial chunk dims only
-            let spatial_chunk_dims: Vec<u32> = chunk_dimensions[..rank].to_vec();
+            let spatial_chunk_dims: &[u32] = &chunk_dimensions[..rank];
            generate_implicit_chunks(
                addr,
                &dataspace.dimensions,
-                &spatial_chunk_dims,
+                spatial_chunk_dims,
                elem_size as u32,
            )
        }
        (4, Some(3)) => {
            // Fixed Array — use spatial chunk dims only
-            let spatial_chunk_dims: Vec<u32> = chunk_dimensions[..rank].to_vec();
+            let spatial_chunk_dims: &[u32] = &chunk_dimensions[..rank];
            let header =
                FixedArrayHeader::parse(file_data, addr as usize, offset_size, length_size)?;
            read_fixed_array_chunks(
                file_data,
                &header,
                &dataspace.dimensions,
-                &spatial_chunk_dims,
+                spatial_chunk_dims,
                elem_size as u32,
                offset_size,
                length_size,
@@ -409,14 +433,14 @@ pub fn read_chunked_data(
        }
        (4, Some(4)) => {
            // Extensible Array — use spatial chunk dims only
-            let spatial_chunk_dims: Vec<u32> = chunk_dimensions[..rank].to_vec();
+            let spatial_chunk_dims: &[u32] = &chunk_dimensions[..rank];
            let header =
                ExtensibleArrayHeader::parse(file_data, addr as usize, offset_size, length_size)?;
            read_extensible_array_chunks(
                file_data,
                &header,
                &dataspace.dimensions,
-                &spatial_chunk_dims,
+                spatial_chunk_dims,
                elem_size as u32,
                offset_size,
                length_size,
@@ -459,12 +483,7 @@ pub fn read_chunked_data(

            let c_addr = chunk_info.address as usize;
            let size = chunk_info.chunk_size as usize;
-            if c_addr + size > file_data.len() {
-                return Err(FormatError::UnexpectedEof {
-                    expected: c_addr + size,
-                    available: file_data.len(),
-                });
-            }
+            ensure_len(file_data, c_addr, size)?;
            let chunk_data = &file_data[c_addr..c_addr + size];

            if rank == 0 {
@@ -577,7 +596,9 @@ pub fn read_chunked_data_cached(

    let elem_size = datatype.type_size() as usize;
    let ndims = chunk_dimensions.len();
-    let rank = ndims - 1;
+    let rank = ndims
+        .checked_sub(1)
+        .ok_or_else(|| FormatError::ChunkedReadError("chunked layout has no dimensions".into()))?;
    let chunk_dims: Vec<usize> = chunk_dimensions[..rank]
        .iter()
        .map(|&d| d as usize)
@@ -616,30 +637,30 @@ pub fn read_chunked_data_cached(
                }]
            }
            (4, Some(2)) => {
-                let spatial_chunk_dims: Vec<u32> = chunk_dimensions[..rank].to_vec();
+                let spatial_chunk_dims: &[u32] = &chunk_dimensions[..rank];
                generate_implicit_chunks(
                    addr,
                    &dataspace.dimensions,
-                    &spatial_chunk_dims,
+                    spatial_chunk_dims,
                    elem_size as u32,
                )
            }
            (4, Some(3)) => {
-                let spatial_chunk_dims: Vec<u32> = chunk_dimensions[..rank].to_vec();
+                let spatial_chunk_dims: &[u32] = &chunk_dimensions[..rank];
                let header =
                    FixedArrayHeader::parse(file_data, addr as usize, offset_size, length_size)?;
                read_fixed_array_chunks(
                    file_data,
                    &header,
                    &dataspace.dimensions,
-                    &spatial_chunk_dims,
+                    spatial_chunk_dims,
                    elem_size as u32,
                    offset_size,
                    length_size,
                )?
            }
            (4, Some(4)) => {
-                let spatial_chunk_dims: Vec<u32> = chunk_dimensions[..rank].to_vec();
+                let spatial_chunk_dims: &[u32] = &chunk_dimensions[..rank];
                let header = ExtensibleArrayHeader::parse(
                    file_data,
                    addr as usize,
@@ -650,7 +671,7 @@ pub fn read_chunked_data_cached(
                    file_data,
                    &header,
                    &dataspace.dimensions,
-                    &spatial_chunk_dims,
+                    spatial_chunk_dims,
                    elem_size as u32,
                    offset_size,
                    length_size,
@@ -689,18 +710,13 @@ pub fn read_chunked_data_cached(
        let coord: Vec<u64> = chunk_info.offsets.iter().take(rank).copied().collect();

        // Try decompressed cache first
-        let decompressed = if let Some(cached) = cache.get_decompressed(&coord) {
+        let decompressed = if let Some(cached) = cache.get_decompressed_aligned(&coord) {
            cached
        } else {
            // Decompress from file
            let c_addr = chunk_info.address as usize;
            let size = chunk_info.chunk_size as usize;
-            if c_addr + size > file_data.len() {
-                return Err(FormatError::UnexpectedEof {
-                    expected: c_addr + size,
-                    available: file_data.len(),
-                });
-            }
+            ensure_len(file_data, c_addr, size)?;
            let raw_chunk = &file_data[c_addr..c_addr + size];
            let dec = if let Some(pl) = pipeline {
                if chunk_info.filter_mask == 0 {
@@ -711,8 +727,7 @@ pub fn read_chunked_data_cached(
            } else {
                raw_chunk.to_vec()
            };
-            cache.put_decompressed(coord, dec.clone());
-            dec
+            cache.put_decompressed(coord, dec)
        };

        let chunk_offsets: Vec<usize> = chunk_info
@@ -934,7 +949,9 @@ pub fn read_chunked_data_sweep(

    let elem_size = datatype.type_size() as usize;
    let ndims = chunk_dimensions.len();
-    let rank = ndims - 1;
+    let rank = ndims
+        .checked_sub(1)
+        .ok_or_else(|| FormatError::ChunkedReadError("chunked layout has no dimensions".into()))?;
    let chunk_dims: Vec<usize> = chunk_dimensions[..rank]
        .iter()
        .map(|&d| d as usize)
@@ -973,30 +990,30 @@ pub fn read_chunked_data_sweep(
                }]
            }
            (4, Some(2)) => {
-                let spatial_chunk_dims: Vec<u32> = chunk_dimensions[..rank].to_vec();
+                let spatial_chunk_dims: &[u32] = &chunk_dimensions[..rank];
                generate_implicit_chunks(
                    addr,
                    &dataspace.dimensions,
-                    &spatial_chunk_dims,
+                    spatial_chunk_dims,
                    elem_size as u32,
                )
            }
            (4, Some(3)) => {
-                let spatial_chunk_dims: Vec<u32> = chunk_dimensions[..rank].to_vec();
+                let spatial_chunk_dims: &[u32] = &chunk_dimensions[..rank];
                let header =
                    FixedArrayHeader::parse(file_data, addr as usize, offset_size, length_size)?;
                read_fixed_array_chunks(
                    file_data,
                    &header,
                    &dataspace.dimensions,
-                    &spatial_chunk_dims,
+                    spatial_chunk_dims,
                    elem_size as u32,
                    offset_size,
                    length_size,
                )?
            }
            (4, Some(4)) => {
-                let spatial_chunk_dims: Vec<u32> = chunk_dimensions[..rank].to_vec();
+                let spatial_chunk_dims: &[u32] = &chunk_dimensions[..rank];
                let header = ExtensibleArrayHeader::parse(
                    file_data,
                    addr as usize,
@@ -1007,7 +1024,7 @@ pub fn read_chunked_data_sweep(
                    file_data,
                    &header,
                    &dataspace.dimensions,
-                    &spatial_chunk_dims,
+                    spatial_chunk_dims,
                    elem_size as u32,
                    offset_size,
                    length_size,
@@ -1055,18 +1072,13 @@ pub fn read_chunked_data_sweep(
        }

        // Try decompressed cache first
-        let decompressed = if let Some(cached) = cache.get_decompressed(&coord) {
+        let decompressed = if let Some(cached) = cache.get_decompressed_aligned(&coord) {
            cached
        } else {
            // Decompress from file
            let c_addr = chunk_info.address as usize;
            let size = chunk_info.chunk_size as usize;
-            if c_addr + size > file_data.len() {
-                return Err(FormatError::UnexpectedEof {
-                    expected: c_addr + size,
-                    available: file_data.len(),
-                });
-            }
+            ensure_len(file_data, c_addr, size)?;
            let raw_chunk = &file_data[c_addr..c_addr + size];
            let dec = if let Some(pl) = pipeline {
                if chunk_info.filter_mask == 0 {
@@ -1077,8 +1089,7 @@ pub fn read_chunked_data_sweep(
            } else {
                raw_chunk.to_vec()
            };
-            cache.put_decompressed(coord, dec.clone());
-            dec
+            cache.put_decompressed(coord, dec)
        };

        let chunk_offsets: Vec<usize> = chunk_info
@@ -1161,7 +1172,9 @@ pub fn read_chunked_data_indexed(

    let elem_size = datatype.type_size() as usize;
    let ndims = chunk_dimensions.len();
-    let rank = ndims - 1;
+    let rank = ndims
+        .checked_sub(1)
+        .ok_or_else(|| FormatError::ChunkedReadError("chunked layout has no dimensions".into()))?;
    let chunk_dims: Vec<usize> = chunk_dimensions[..rank]
        .iter()
        .map(|&d| d as usize)
@@ -1200,30 +1213,30 @@ pub fn read_chunked_data_indexed(
                }]
            }
            (4, Some(2)) => {
-                let spatial_chunk_dims: Vec<u32> = chunk_dimensions[..rank].to_vec();
+                let spatial_chunk_dims: &[u32] = &chunk_dimensions[..rank];
                generate_implicit_chunks(
                    addr,
                    &dataspace.dimensions,
-                    &spatial_chunk_dims,
+                    spatial_chunk_dims,
                    elem_size as u32,
                )
            }
            (4, Some(3)) => {
-                let spatial_chunk_dims: Vec<u32> = chunk_dimensions[..rank].to_vec();
+                let spatial_chunk_dims: &[u32] = &chunk_dimensions[..rank];
                let header =
                    FixedArrayHeader::parse(file_data, addr as usize, offset_size, length_size)?;
                read_fixed_array_chunks(
                    file_data,
                    &header,
                    &dataspace.dimensions,
-                    &spatial_chunk_dims,
+                    spatial_chunk_dims,
                    elem_size as u32,
                    offset_size,
                    length_size,
                )?
            }
            (4, Some(4)) => {
-                let spatial_chunk_dims: Vec<u32> = chunk_dimensions[..rank].to_vec();
+                let spatial_chunk_dims: &[u32] = &chunk_dimensions[..rank];
                let header = ExtensibleArrayHeader::parse(
                    file_data,
                    addr as usize,
@@ -1234,7 +1247,7 @@ pub fn read_chunked_data_indexed(
                    file_data,
                    &header,
                    &dataspace.dimensions,
-                    &spatial_chunk_dims,
+                    spatial_chunk_dims,
                    elem_size as u32,
                    offset_size,
                    length_size,
@@ -1271,19 +1284,14 @@ pub fn read_chunked_data_indexed(
        .ok_or_else(|| FormatError::ChunkedReadError("chunk layout not available".into()))?;

    // Decompress chunks (using LRU cache where possible)
-    let mut chunk_buffers: Vec<CacheAlignedBuffer> = Vec::with_capacity(mappings_info.len());
+    let mut chunk_buffers: Vec<Arc<CacheAlignedBuffer>> = Vec::with_capacity(mappings_info.len());
    for (coord, file_offset, file_size, filter_mask) in &mappings_info {
        if let Some(cached) = cache.get_decompressed_aligned(coord) {
            chunk_buffers.push(cached);
        } else {
            let c_addr = *file_offset as usize;
            let size = *file_size as usize;
-            if c_addr + size > file_data.len() {
-                return Err(FormatError::UnexpectedEof {
-                    expected: c_addr + size,
-                    available: file_data.len(),
-                });
-            }
+            ensure_len(file_data, c_addr, size)?;
            let raw_chunk = &file_data[c_addr..c_addr + size];
            let decompressed = if let Some(pl) = pipeline {
                if *filter_mask == 0 {
@@ -1295,8 +1303,8 @@ pub fn read_chunked_data_indexed(
                raw_chunk.to_vec()
            };
            let aligned = CacheAlignedBuffer::from_vec(decompressed);
-            cache.put_decompressed_aligned(coord.clone(), aligned.clone());
-            chunk_buffers.push(aligned);
+            let arc = cache.put_decompressed_aligned(coord.clone(), aligned);
+            chunk_buffers.push(arc);
        }
    }

@@ -1331,9 +1339,18 @@ fn copy_chunk_to_output(
        // Fast path for 1-D: single contiguous copy per chunk
        let global_start = chunk_offsets[0];
        let copy_len = chunk_dims[0].min(ds_dims[0].saturating_sub(global_start));
-        let src_bytes = copy_len * elem_size;
-        let dst_start = global_start * elem_size;
-        if src_bytes > 0 && dst_start + src_bytes <= output.len() && src_bytes <= chunk_data.len() {
+        let (Some(src_bytes), Some(dst_start)) = (
+            copy_len.checked_mul(elem_size),
+            global_start.checked_mul(elem_size),
+        ) else {
+            return;
+        };
+        if src_bytes > 0
+            && dst_start
+                .checked_add(src_bytes)
+                .is_some_and(|end| end <= output.len())
+            && src_bytes <= chunk_data.len()
+        {
            output[dst_start..dst_start + src_bytes].copy_from_slice(&chunk_data[..src_bytes]);
        }
        return;
@@ -1343,19 +1360,29 @@ fn copy_chunk_to_output(
    let inner_dim = rank - 1;
    let inner_chunk_len =
        chunk_dims[inner_dim].min(ds_dims[inner_dim].saturating_sub(chunk_offsets[inner_dim]));
-    let row_bytes = inner_chunk_len * elem_size;
+    let Some(row_bytes) = inner_chunk_len.checked_mul(elem_size) else {
+        return;
+    };

    if row_bytes == 0 {
        return;
    }

    // Number of rows = product of all outer chunk dimensions
-    let outer_count: usize = chunk_dims[..inner_dim].iter().product();
+    let Some(outer_count) = chunk_dims[..inner_dim]
+        .iter()
+        .try_fold(1usize, |acc, &d| acc.checked_mul(d))
+    else {
+        return;
+    };

    // Outer strides for iterating chunk-local coordinates
    let mut outer_strides = vec![1usize; inner_dim];
    for i in (0..inner_dim.saturating_sub(1)).rev() {
-        outer_strides[i] = outer_strides[i + 1] * chunk_dims[i + 1];
+        let Some(stride) = outer_strides[i + 1].checked_mul(chunk_dims[i + 1]) else {
+            return;
+        };
+        outer_strides[i] = stride;
    }

    for outer_idx in 0..outer_count {
@@ -1375,13 +1402,29 @@ fn copy_chunk_to_output(
                remaining %= outer_strides[d];
            }

-            let global_coord = chunk_offsets[d] + coord_in_chunk;
+            let Some(global_coord) = chunk_offsets[d].checked_add(coord_in_chunk) else {
+                out_of_bounds = true;
+                break;
+            };
            if global_coord >= ds_dims[d] {
                out_of_bounds = true;
                break;
            }
-            ds_flat += global_coord * ds_strides[d];
-            src_flat += coord_in_chunk * chunk_strides[d];
+            let (Some(ds_term), Some(src_term)) = (
+                global_coord.checked_mul(ds_strides[d]),
+                coord_in_chunk.checked_mul(chunk_strides[d]),
+            ) else {
+                out_of_bounds = true;
+                break;
+            };
+            let (Some(new_ds_flat), Some(new_src_flat)) =
+                (ds_flat.checked_add(ds_term), src_flat.checked_add(src_term))
+            else {
+                out_of_bounds = true;
+                break;
+            };
+            ds_flat = new_ds_flat;
+            src_flat = new_src_flat;
        }

        if out_of_bounds {
@@ -1389,12 +1432,27 @@ fn copy_chunk_to_output(
        }

        // Add innermost dimension offset
-        ds_flat += chunk_offsets[inner_dim] * ds_strides[inner_dim];
+        let Some(inner_term) = chunk_offsets[inner_dim].checked_mul(ds_strides[inner_dim]) else {
+            continue;
+        };
+        let Some(ds_flat) = ds_flat.checked_add(inner_term) else {
+            continue;
+        };

-        let src_start = src_flat * elem_size;
-        let dst_start = ds_flat * elem_size;
+        let (Some(src_start), Some(dst_start)) = (
+            src_flat.checked_mul(elem_size),
+            ds_flat.checked_mul(elem_size),
+        ) else {
+            continue;
+        };

-        if src_start + row_bytes <= chunk_data.len() && dst_start + row_bytes <= output.len() {
+        let fits = src_start
+            .checked_add(row_bytes)
+            .is_some_and(|end| end <= chunk_data.len())
+            && dst_start
+                .checked_add(row_bytes)
+                .is_some_and(|end| end <= output.len());
+        if fits {
            output[dst_start..dst_start + row_bytes]
                .copy_from_slice(&chunk_data[src_start..src_start + row_bytes]);
        }
@@ -1639,6 +1697,82 @@ mod tests {
        (file_data, layout, dataspace)
    }

+    #[test]
+    fn read_chunked_data_rejects_zero_dim_chunk_layout() {
+        // Found by fuzzing: chunk_dimensions.len() == 0 caused `ndims - 1` to
+        // underflow. A malformed/degenerate chunked layout must error cleanly.
+        let layout = DataLayout::Chunked {
+            chunk_dimensions: vec![],
+            btree_address: Some(0),
+            version: 3,
+            chunk_index_type: None,
+            single_chunk_filtered_size: None,
+            single_chunk_filter_mask: None,
+        };
+        let dataspace = Dataspace {
+            space_type: DataspaceType::Simple,
+            rank: 1,
+            dimensions: vec![10],
+            max_dimensions: None,
+        };
+        let datatype = make_f64_type();
+        let file_data = vec![0u8; 64];
+        let result = read_chunked_data(&file_data, &layout, &dataspace, &datatype, None, 8, 8);
+        assert!(
+            matches!(result, Err(FormatError::ChunkedReadError(_))),
+            "expected a clean ChunkedReadError, got {result:?}"
+        );
+    }
+
+    #[test]
+    fn copy_chunk_to_output_1d_rejects_overflowing_offset_without_panicking() {
+        // Found by fuzzing: `global_start * elem_size` overflowed for a
+        // crafted large chunk offset.
+        let chunk_data = vec![1u8; 16];
+        let mut output = vec![0u8; 16];
+        let chunk_offsets = [usize::MAX - 1];
+        let chunk_dims = [1usize];
+        let ds_dims = [usize::MAX];
+        let ds_strides = [1usize];
+        let chunk_strides = [1usize];
+        copy_chunk_to_output(
+            &chunk_data,
+            &mut output,
+            &chunk_offsets,
+            &chunk_dims,
+            &ds_dims,
+            &ds_strides,
+            &chunk_strides,
+            8,
+            1,
+        );
+        // No panic; the out-of-range write was skipped, output left untouched.
+        assert_eq!(output, vec![0u8; 16]);
+    }
+
+    #[test]
+    fn copy_chunk_to_output_nd_rejects_overflowing_offset_without_panicking() {
+        let chunk_data = vec![1u8; 16];
+        let mut output = vec![0u8; 16];
+        let chunk_offsets = [usize::MAX - 1, 0];
+        let chunk_dims = [1usize, 1usize];
+        let ds_dims = [usize::MAX, usize::MAX];
+        let ds_strides = [1usize, 1usize];
+        let chunk_strides = [1usize, 1usize];
+        copy_chunk_to_output(
+            &chunk_data,
+            &mut output,
+            &chunk_offsets,
+            &chunk_dims,
+            &ds_dims,
+            &ds_strides,
+            &chunk_strides,
+            8,
+            2,
+        );
+        assert_eq!(output, vec![0u8; 16]);
+    }
+
    #[test]
    fn read_1d_two_chunks_no_compression() {
        let values: Vec<f64> = (0..20).map(|i| i as f64).collect();
@@ -1851,6 +1985,54 @@ mod tests {
        assert_eq!(err, FormatError::InvalidBTreeNodeType(0));
    }

+    #[test]
+    fn collect_chunk_info_rejects_near_usize_max_offset() {
+        let file_data = vec![0u8; 64];
+        let result = collect_chunk_info(&file_data, u64::MAX - 4, 2, 8, 8);
+        assert!(
+            matches!(result, Err(FormatError::UnexpectedEof { .. })),
+            "expected a clean UnexpectedEof, got {result:?}"
+        );
+    }
+
+    #[test]
+    fn collect_chunk_info_rejects_self_referencing_internal_node() {
+        // A type-1 internal node (level 1) whose single child address points
+        // back to itself: an infinite-recursion / cyclic B-tree attack.
+        let ndims = 2;
+        let os: u8 = 8;
+        let mut buf = Vec::new();
+        buf.extend_from_slice(b"TREE");
+        buf.push(1); // node_type = 1 (raw data chunks)
+        buf.push(1); // node_level = 1 (internal)
+        buf.extend_from_slice(&1u16.to_le_bytes()); // entries_used = 1
+        write_offset(&mut buf, u64::MAX, os); // left sibling undefined
+        write_offset(&mut buf, u64::MAX, os); // right sibling undefined
+        // key[0]: chunk_size(4) + filter_mask(4) + ndims offsets
+        buf.extend_from_slice(&0u32.to_le_bytes());
+        buf.extend_from_slice(&0u32.to_le_bytes());
+        for _ in 0..ndims {
+            write_offset(&mut buf, 0, os);
+        }
+        // child[0]: points back to offset 0 (this same node) — cyclic.
+        write_offset(&mut buf, 0, os);
+        // final key
+        buf.extend_from_slice(&0u32.to_le_bytes());
+        buf.extend_from_slice(&0u32.to_le_bytes());
+        for _ in 0..ndims {
+            write_offset(&mut buf, u64::MAX, os);
+        }
+
+        let mut file_data = vec![0u8; 256];
+        file_data[..buf.len()].copy_from_slice(&buf);
+
+        let result = collect_chunk_info(&file_data, 0, ndims, os, os);
+        assert!(
+            matches!(result, Err(FormatError::NestingDepthExceeded)),
+            "expected a clean NestingDepthExceeded, got {result:?}"
+        );
+    }
+
    // --- Implicit chunk generation tests ---

    #[test]
@@ -65,10 +65,8 @@ impl ChunkOptions {
    pub fn build_pipeline(&self, element_size: u32) -> Option<FilterPipeline> {
        let mut filters = Vec::new();

-        let has_compression = self.deflate_level.is_some()
-            || self.zstd_level.is_some()
-            || self.lz4
-            || self.pcodec;
+        let has_compression =
+            self.deflate_level.is_some() || self.zstd_level.is_some() || self.lz4 || self.pcodec;

        // Shuffle before compression. Applied if explicitly requested OR if compression
        // is active and the caller hasn't disabled it — matches h5py default behavior
@@ -608,7 +606,7 @@ pub fn precompress_chunks(

    let chunks = raw_chunks
        .into_iter()
-        .zip(compressed.into_iter())
+        .zip(compressed)
        .map(|((_offsets, raw_bytes), c)| (raw_bytes.len() as u64, c))
        .collect();

@@ -755,7 +753,11 @@ pub fn build_chunked_data_at_ext(
    maxshape: Option<&[u64]>,
 ) -> Result<ChunkedDataResult, FormatError> {
    let pre = precompress_chunks(raw_data, shape, chunk_dims, element_size, options)?;
-    Ok(build_chunked_data_from_precompressed(&pre, base_address, maxshape))
+    Ok(build_chunked_data_from_precompressed(
+        &pre,
+        base_address,
+        maxshape,
+    ))
 }

 /// Write selected elements into an existing in-memory dataset buffer.
@@ -821,7 +821,8 @@ mod tests {
        let blob = [
            0x00u8, // block version 0
            0x01, 0, 0, 0, 0, 0, 0, 0, // nused = 1
-            0x73, 0x72, 0x63, 0x5f, 0x65, 0x78, 0x74, 0x2e, 0x68, 0x35, 0x00, // "src_ext.h5\0"
+            0x73, 0x72, 0x63, 0x5f, 0x65, 0x78, 0x74, 0x2e, 0x68, 0x35,
+            0x00, // "src_ext.h5\0"
            0x64, 0x61, 0x74, 0x61, 0x00, // "data\0"
            0x03, 0, 0, 0, 0x01, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, // source sel = ALL
            0x03, 0, 0, 0, 0x01, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, // virtual sel = ALL
@@ -846,7 +847,7 @@ mod tests {
        // One entry whose source selection (ALL) is truncated to 8 of 16 bytes.
        let blob = [
            0x01u8, // version 1
-            0x01, 0, 0, 0, 0, 0, 0, 0, // nused = 1
+            0x01, 0, 0, 0, 0, 0, 0, 0,    // nused = 1
            0x04, // same-file marker
            0x78, 0x00, // "x\0"
            0x03, 0, 0, 0, 0x01, 0, 0, 0, // ALL header, truncated (8 of 16 bytes)
@@ -17,6 +17,21 @@ use crate::datatype::{Datatype, DatatypeByteOrder};
 use crate::error::FormatError;
 use crate::filter_pipeline::FilterPipeline;

+/// Checks that `[offset, offset + needed)` fits within `data`, guarding the
+/// addition against `usize` overflow from a crafted near-`usize::MAX` offset.
+fn ensure_len(data: &[u8], offset: usize, needed: usize) -> Result<(), FormatError> {
+    if offset
+        .checked_add(needed)
+        .is_none_or(|end| end > data.len())
+    {
+        return Err(FormatError::UnexpectedEof {
+            expected: offset.saturating_add(needed),
+            available: data.len(),
+        });
+    }
+    Ok(())
+}
+
 /// Zero-copy read of contiguous raw data, returning a borrowed slice.
 ///
 /// For contiguous layouts, returns a direct `&[u8]` slice into `file_data`.
@@ -47,12 +62,7 @@ pub fn read_raw_data_zerocopy<'a>(
                    actual: sz,
                });
            }
-            if addr + sz > file_data.len() {
-                return Err(FormatError::UnexpectedEof {
-                    expected: addr + sz,
-                    available: file_data.len(),
-                });
-            }
+            ensure_len(file_data, addr, sz)?;
            Ok(Some(&file_data[addr..addr + sz]))
        }
        _ => Ok(None),
@@ -94,7 +104,14 @@ pub fn read_raw_data_full(
    length_size: u8,
 ) -> Result<Vec<u8>, FormatError> {
    read_raw_data_full_impl(
-        file_data, layout, dataspace, datatype, pipeline, offset_size, length_size, None,
+        file_data,
+        layout,
+        dataspace,
+        datatype,
+        pipeline,
+        offset_size,
+        length_size,
+        None,
    )
 }

@@ -112,7 +129,14 @@ pub fn read_raw_data_full_with_resolver(
    resolver: Option<&VdsSourceResolver>,
 ) -> Result<Vec<u8>, FormatError> {
    read_raw_data_full_impl(
-        file_data, layout, dataspace, datatype, pipeline, offset_size, length_size, resolver,
+        file_data,
+        layout,
+        dataspace,
+        datatype,
+        pipeline,
+        offset_size,
+        length_size,
+        resolver,
    )
 }

@@ -155,12 +179,7 @@ fn read_raw_data_full_impl(
                    actual: sz,
                });
            }
-            if addr + sz > file_data.len() {
-                return Err(FormatError::UnexpectedEof {
-                    expected: addr + sz,
-                    available: file_data.len(),
-                });
-            }
+            ensure_len(file_data, addr, sz)?;
            Ok(file_data[addr..addr + sz].to_vec())
        }
        DataLayout::Chunked { .. } => read_chunked_data(
@@ -465,12 +484,12 @@ fn read_virtual_data(
        FormatError::ChunkedReadError("virtual dataset has no mapping global heap".into())
    })?;
    let coll = GlobalHeapCollection::parse(file_data, addr as usize, length_size)?;
-    let obj = coll
-        .get_object(global_heap_index as u16)
-        .ok_or(FormatError::GlobalHeapObjectNotFound {
-            collection_address: addr,
-            index: global_heap_index as u16,
-        })?;
+    let obj =
+        coll.get_object(global_heap_index as u16)
+            .ok_or(FormatError::GlobalHeapObjectNotFound {
+                collection_address: addr,
+                index: global_heap_index as u16,
+            })?;
    let mappings = parse_vds_mappings(&obj.data, length_size)?;

    for m in &mappings {
@@ -1204,6 +1223,15 @@ pub fn read_compound_fields(
            for m in members {
                let field_size = m.datatype.type_size() as usize;
                let offset = m.byte_offset as usize;
+                if offset
+                    .checked_add(field_size)
+                    .is_none_or(|end| end > elem_size)
+                {
+                    return Err(FormatError::Overflow(format!(
+                        "compound member '{}': byte_offset({offset}) + field_size({field_size}) exceeds element size({elem_size})",
+                        m.name
+                    )));
+                }
                let mut field_raw = Vec::with_capacity(count * field_size);
                for i in 0..count {
                    let elem_start = i * elem_size + offset;
@@ -1815,13 +1843,19 @@ mod tests {
            0xff, 0xff, 0x00, 0x00, 0x64, 0x00, 0x00, 0x00, 0xe8, 0x03, 0x00, 0x00, 0x00, 0x80,
            0x00, 0x00,
        ];
-        assert_eq!(read_as_i32(&raw, &arr).unwrap(), vec![-1, 100, 1000, -32768]);
+        assert_eq!(
+            read_as_i32(&raw, &arr).unwrap(),
+            vec![-1, 100, 1000, -32768]
+        );
        // Nested array-of-array unwraps recursively.
        let nested = Datatype::Array {
            base_type: Box::new(arr),
            dimensions: vec![2],
        };
-        assert_eq!(read_as_i32(&raw, &nested).unwrap(), vec![-1, 100, 1000, -32768]);
+        assert_eq!(
+            read_as_i32(&raw, &nested).unwrap(),
+            vec![-1, 100, 1000, -32768]
+        );
    }

    fn make_f64_le_type() -> Datatype {
@@ -2096,6 +2130,43 @@ mod tests {
        assert_eq!(id_vals, vec![10, 20]);
    }

+    #[test]
+    fn read_compound_rejects_byte_offset_overrun() {
+        use crate::datatype::CompoundMember;
+        // Compound declares size=8, but the member's byte_offset(4) + its
+        // field_size(8, f64) = 12 > 8 — a crafted out-of-range byte_offset.
+        let dt = Datatype::Compound {
+            size: 8,
+            members: vec![CompoundMember {
+                name: "bad".to_string(),
+                byte_offset: 4,
+                datatype: make_f64_le_type(),
+            }],
+        };
+        let raw = vec![0u8; 8]; // one element, matches declared size
+        let result = read_compound_fields(&raw, &dt);
+        assert!(
+            matches!(result, Err(FormatError::Overflow(_))),
+            "expected a clean Overflow error, got {result:?}"
+        );
+    }
+
+    #[test]
+    fn read_raw_data_zerocopy_rejects_near_usize_max_offset() {
+        let file_data = vec![0u8; 64];
+        let dataspace = make_simple_dataspace(&[4]);
+        let datatype = make_i32_le_type();
+        let layout = DataLayout::Contiguous {
+            address: Some(u64::MAX - 4),
+            size: 16,
+        };
+        let result = read_raw_data_zerocopy(&file_data, &layout, &dataspace, &datatype);
+        assert!(
+            matches!(result, Err(FormatError::UnexpectedEof { .. })),
+            "expected a clean UnexpectedEof, got {result:?}"
+        );
+    }
+
    #[test]
    fn read_compound_single_field_by_name() {
        use crate::datatype::CompoundMember;
@@ -1030,14 +1030,8 @@ mod tests {
            Datatype::Compound { size, members } => {
                assert_eq!(size, 20);
                assert_eq!(members.len(), 3);
-                assert_eq!(
-                    (members[0].name.as_str(), members[0].byte_offset),
-                    ("x", 0)
-                );
-                assert_eq!(
-                    (members[1].name.as_str(), members[1].byte_offset),
-                    ("y", 8)
-                );
+                assert_eq!((members[0].name.as_str(), members[0].byte_offset), ("x", 0));
+                assert_eq!((members[1].name.as_str(), members[1].byte_offset), ("y", 8));
                assert_eq!(
                    (members[2].name.as_str(), members[2].byte_offset),
                    ("id", 16)
@@ -1076,7 +1070,10 @@ mod tests {
                dimensions,
            } => {
                assert_eq!(dimensions, vec![3]);
-                assert!(matches!(*base_type, Datatype::FloatingPoint { size: 8, .. }));
+                assert!(matches!(
+                    *base_type,
+                    Datatype::FloatingPoint { size: 8, .. }
+                ));
            }
            other => panic!("expected Array, got {other:?}"),
        }
@@ -20,7 +20,7 @@
 //! ```

 #[cfg(not(feature = "std"))]
-use alloc::{string::String, vec, vec::Vec};
+use alloc::{format, string::String, vec, vec::Vec};

 #[cfg(not(feature = "std"))]
 use alloc::collections::BTreeMap;
@@ -375,7 +375,8 @@ fn build_multiblock_fractal_heap(
    let table_width: u16 = 4;
    let starting_block_size: u64 = 512;
    let dblock_header_size = 4 + 1 + os + block_offset_bytes + 4;
-    let block_capacity = |row: usize| block_size_for_row(starting_block_size, row) - dblock_header_size as u64;
+    let block_capacity =
+        |row: usize| block_size_for_row(starting_block_size, row) - dblock_header_size as u64;

    // ---- Pack objects into direct blocks (row-major over the doubling table) ----
    struct Blk {
@@ -542,7 +543,26 @@ fn block_size_for_row(starting_block_size: u64, row: usize) -> u64 {

 /// Size in bytes of the FRHP header for the given offset/length sizes.
 fn frhp_header_size(os: usize, ls: usize) -> usize {
-    4 + 1 + 2 + 2 + 1 + 4 + ls + os + ls + os + ls + ls + ls + ls + ls + ls + ls + ls + 2 + ls + ls
+    4 + 1
+        + 2
+        + 2
+        + 1
+        + 4
+        + ls
+        + os
+        + ls
+        + os
+        + ls
+        + ls
+        + ls
+        + ls
+        + ls
+        + ls
+        + ls
+        + ls
+        + 2
+        + ls
+        + ls
        + 2
        + 2
        + os
@@ -670,8 +690,7 @@ pub(crate) fn build_dense_attrs(attrs: &[AttributeMessage], base_address: u64) -
    // Pad to node_size
    btlf.resize(node_size as usize, 0);

-    let mut blob =
-        Vec::with_capacity(heap.blob.len() + bthd.len() + btlf.len());
+    let mut blob = Vec::with_capacity(heap.blob.len() + bthd.len() + btlf.len());
    blob.extend_from_slice(&heap.blob);
    blob.extend_from_slice(&bthd);
    blob.extend_from_slice(&btlf);
@@ -762,8 +781,7 @@ pub(crate) fn build_dense_links(links: &[LinkMessage], base_address: u64) -> Den
    btlf.extend_from_slice(&btlf_checksum.to_le_bytes());
    btlf.resize(node_size as usize, 0);

-    let mut blob =
-        Vec::with_capacity(heap.blob.len() + bthd.len() + btlf.len());
+    let mut blob = Vec::with_capacity(heap.blob.len() + bthd.len() + btlf.len());
    blob.extend_from_slice(&heap.blob);
    blob.extend_from_slice(&bthd);
    blob.extend_from_slice(&btlf);
@@ -1096,10 +1114,7 @@ impl FileWriter {
            root_attrs.push(build_attr_message(n, v));
        }

-        let is_vds: Vec<bool> = all_ds
-            .iter()
-            .map(|d| d.virtual_sources.is_some())
-            .collect();
+        let is_vds: Vec<bool> = all_ds.iter().map(|d| d.virtual_sources.is_some()).collect();
        let is_chunked: Vec<bool> = all_ds
            .iter()
            .enumerate()
@@ -1198,7 +1213,8 @@ impl FileWriter {
                // Global heap blob size is address-independent; compute it now
                // so pass 2 can place it correctly.
                let vds_mappings = d.virtual_sources.as_deref().unwrap_or(&[]);
-                let gcol_bytes = build_global_heap_collection(&serialize_vds_mappings(vds_mappings));
+                let gcol_bytes =
+                    build_global_heap_collection(&serialize_vds_mappings(vds_mappings));
                dummy_blobs.push(DataBlob {
                    data: gcol_bytes, // store heap blob here temporarily
                    oh_bytes: oh,
@@ -1216,8 +1232,11 @@ impl FileWriter {
                    elem_size,
                    &d.chunk_options,
                )?;
-                let result =
-                    build_chunked_data_from_precompressed(&pre, dummy_cursor, d.maxshape.as_deref());
+                let result = build_chunked_data_from_precompressed(
+                    &pre,
+                    dummy_cursor,
+                    d.maxshape.as_deref(),
+                );
                dummy_cursor += result.data_bytes.len() as u64;
                let dense_blob = if ds_dense[i] {
                    Some(build_dense_attrs(&d.attrs, 0))
@@ -1391,7 +1410,10 @@ impl FileWriter {
                // Reuse precompressed chunks from Pass 1 — avoids re-compressing
                // the same data a second time.
                let result = build_chunked_data_from_precompressed(
-                    dummy_blobs[i].precompressed.as_ref().expect("chunked dataset missing precompressed cache"),
+                    dummy_blobs[i]
+                        .precompressed
+                        .as_ref()
+                        .expect("chunked dataset missing precompressed cache"),
                    base_address,
                    d.maxshape.as_deref(),
                );
@@ -1492,7 +1514,9 @@ impl FileWriter {
        // Rebuild the root link blob with real target addresses (same size as
        // the dummy used for layout); its LinkInfo goes in the OH.
        let root_link_blob = root_link_blob_addr.map(|addr| build_dense_links(&root_links, addr));
-        let root_dl = root_link_blob.as_ref().map(|b| b.link_info_message.as_slice());
+        let root_dl = root_link_blob
+            .as_ref()
+            .map(|b| b.link_info_message.as_slice());
        buf.extend_from_slice(&build_group_oh(
            &root_links,
            root_dl,
@@ -1903,14 +1927,14 @@ mod tests {
    fn sel_hyper_1d(start: u16, block: u16) -> Vec<u8> {
        let mut v = vec![
            2, 0, 0, 0, // type = HYPER
-            3, 0, 0, 0, // version 3
-            0x01,       // flags = regular
-            0x02,       // enc_size = 2 (u16 per coordinate)
+            3, 0, 0, 0,    // version 3
+            0x01, // flags = regular
+            0x02, // enc_size = 2 (u16 per coordinate)
            1, 0, 0, 0, // rank = 1
        ];
        v.extend_from_slice(&start.to_le_bytes()); // start
-        v.extend_from_slice(&1u16.to_le_bytes());  // stride
-        v.extend_from_slice(&1u16.to_le_bytes());  // count
+        v.extend_from_slice(&1u16.to_le_bytes()); // stride
+        v.extend_from_slice(&1u16.to_le_bytes()); // count
        v.extend_from_slice(&block.to_le_bytes()); // block
        v
    }
@@ -1936,8 +1960,10 @@ mod tests {

        let mut fw = FileWriter::new();
        // Source datasets (real data in this file)
-        fw.create_dataset("src_a").with_f64_data(&[1.0, 2.0, 3.0, 4.0]);
-        fw.create_dataset("src_b").with_f64_data(&[5.0, 6.0, 7.0, 8.0]);
+        fw.create_dataset("src_a")
+            .with_f64_data(&[1.0, 2.0, 3.0, 4.0]);
+        fw.create_dataset("src_b")
+            .with_f64_data(&[5.0, 6.0, 7.0, 8.0]);
        // Virtual dataset
        fw.create_dataset("vds")
            .with_shape(&[8])
@@ -1950,13 +1976,8 @@ mod tests {
        let sig = signature::find_signature(&bytes).unwrap();
        let sb = Superblock::parse(&bytes, sig).unwrap();
        let vds_addr = resolve_path_any(&bytes, &sb, "vds").unwrap();
-        let hdr = ObjectHeader::parse(
-            &bytes,
-            vds_addr as usize,
-            sb.offset_size,
-            sb.length_size,
-        )
-        .unwrap();
+        let hdr =
+            ObjectHeader::parse(&bytes, vds_addr as usize, sb.offset_size, sb.length_size).unwrap();

        let dl_data = &hdr
            .messages
@@ -1965,8 +1986,7 @@ mod tests {
            .unwrap()
            .data;

-        let mut layout =
-            DataLayout::parse(dl_data, sb.offset_size, sb.length_size).unwrap();
+        let mut layout = DataLayout::parse(dl_data, sb.offset_size, sb.length_size).unwrap();

        // Before resolution, mappings field is empty.
        assert!(
@@ -2033,8 +2053,7 @@ mod tests {
            .find(|m| m.msg_type == MessageType::DataLayout)
            .unwrap()
            .data;
-        let mut layout =
-            DataLayout::parse(dl_data, sb.offset_size, sb.length_size).unwrap();
+        let mut layout = DataLayout::parse(dl_data, sb.offset_size, sb.length_size).unwrap();
        layout.resolve_vds_mappings(&bytes, sb.length_size).unwrap();

        match &layout {
@@ -2112,7 +2131,10 @@ mod tests {
            .expect("external link 'remote_temp' not found in group OH");

        match &ext_link.link_target {
-            crate::link_message::LinkTarget::External { filename, object_path } => {
+            crate::link_message::LinkTarget::External {
+                filename,
+                object_path,
+            } => {
                assert_eq!(filename, "other_file.h5");
                assert_eq!(object_path, "/temperature");
            }
@@ -4,14 +4,19 @@
 extern crate alloc;

 #[cfg(not(feature = "std"))]
-use alloc::{vec, vec::Vec};
+use alloc::{boxed::Box, vec, vec::Vec};

 use crate::error::FormatError;
 use crate::filter_pipeline::{
-    FILTER_DEFLATE, FILTER_FLETCHER32, FILTER_LZ4, FILTER_NBIT, FILTER_PCODEC,
-    FILTER_SCALEOFFSET, FILTER_SHUFFLE, FILTER_SZIP, FILTER_ZSTD, FilterPipeline,
+    FILTER_DEFLATE, FILTER_FLETCHER32, FILTER_LZ4, FILTER_NBIT, FILTER_PCODEC, FILTER_SCALEOFFSET,
+    FILTER_SHUFFLE, FILTER_SZIP, FILTER_ZSTD, FilterPipeline,
 };

+/// Absolute ceiling on a single decompressed chunk's output size, used only
+/// when the pipeline's declared `chunk_size` is unavailable (0). Prevents
+/// unbounded-allocation DoS from a malicious/corrupted compressed chunk.
+pub(crate) const MAX_DECOMPRESS_SIZE: usize = 256 * 1024 * 1024;
+
 /// Apply a filter pipeline to decompress a chunk.
 /// Filters are applied in REVERSE order for decompression.
 pub fn decompress_chunk(
@@ -25,16 +30,22 @@ pub fn decompress_chunk(
    for filter in pipeline.filters.iter().rev() {
        data = match filter.filter_id {
            FILTER_SHUFFLE => shuffle_decompress(&data, element_size as usize)?,
-            FILTER_DEFLATE => deflate_decompress(&data)?,
-            FILTER_LZ4 => lz4_decompress(&data)?,
-            FILTER_ZSTD => zstd_decompress(&data)?,
+            // `chunk_size` is the expected decompressed size (shuffle/fletcher32
+            // are size-preserving, so it bounds these too); pass it so these
+            // decoders can't be forced into unbounded allocation by a hostile
+            // or corrupted compressed payload.
+            FILTER_DEFLATE => deflate_decompress(&data, chunk_size)?,
+            FILTER_LZ4 => lz4_decompress(&data, chunk_size)?,
+            FILTER_ZSTD => zstd_decompress(&data, chunk_size)?,
            FILTER_FLETCHER32 => fletcher32_verify(&data)?,
-            FILTER_PCODEC => pcodec_decompress(&data, element_size as usize)?,
+            FILTER_PCODEC => pcodec_decompress(&data, element_size as usize, chunk_size)?,
            // `chunk_size` is the expected decompressed size; pass it so these
            // decoders can reject an element count that would over-allocate.
            FILTER_SCALEOFFSET => scaleoffset_decompress(&data, &filter.client_data, chunk_size)?,
            FILTER_NBIT => nbit_decompress(&data, &filter.client_data, chunk_size)?,
-            FILTER_SZIP => crate::filters_szip::szip_decompress(&data, &filter.client_data, chunk_size)?,
+            FILTER_SZIP => {
+                crate::filters_szip::szip_decompress(&data, &filter.client_data, chunk_size)?
+            }
            other => return Err(FormatError::UnsupportedFilter(other)),
        };
    }
@@ -89,6 +100,27 @@ pub fn compress_chunk(
 /// E-scale, interpreted as i32 for negative exponents), `[2]`=element count,
 /// `[4]`=element size, `[5]`=signed flag, `[6]`=byte order (1 = big-endian),
 /// `[7]`=fill defined, `[8..]`=fill value bits.
+/// `f64::powi` equivalent that works under `no_std` (no libm/std available).
+/// Exponentiation by squaring, matching `powi`'s semantics for negative
+/// exponents via reciprocal.
+fn powi_f64(base: f64, mut exp: i32) -> f64 {
+    let neg = exp < 0;
+    if neg {
+        exp = -exp;
+    }
+    let mut result = 1.0f64;
+    let mut b = base;
+    let mut e = exp as u32;
+    while e > 0 {
+        if e & 1 == 1 {
+            result *= b;
+        }
+        b *= b;
+        e >>= 1;
+    }
+    if neg { 1.0 / result } else { result }
+}
+
 fn scaleoffset_decompress(
    data: &[u8],
    cd: &[u32],
@@ -207,9 +239,9 @@ fn scaleoffset_decompress(
                if has_fill_code && code == fill_code {
                    fill_value
                } else if is_escale {
-                    minval + code as f64 * 2f64.powi(scale_factor)
+                    minval + code as f64 * powi_f64(2.0, scale_factor)
                } else {
-                    minval + code as f64 / 10f64.powi(scale_factor)
+                    minval + code as f64 / powi_f64(10.0, scale_factor)
                }
            })
            .collect();
@@ -569,24 +601,48 @@ fn nbit_decompress(data: &[u8], cd: &[u32], expected_bytes: usize) -> Result<Vec
 }

 /// Decompress zlib-compressed data.
+///
+/// `expected_bytes` is the pipeline's declared decompressed chunk size (0 if
+/// unavailable); output is rejected if it exceeds this bound (or, when
+/// unavailable, [`MAX_DECOMPRESS_SIZE`]), preventing a hostile/corrupted
+/// compressed payload from forcing unbounded allocation (a "zlib bomb").
 #[cfg(feature = "deflate")]
-fn deflate_decompress(data: &[u8]) -> Result<Vec<u8>, FormatError> {
+fn deflate_decompress(data: &[u8], expected_bytes: usize) -> Result<Vec<u8>, FormatError> {
+    let limit = if expected_bytes != 0 {
+        expected_bytes
+    } else {
+        MAX_DECOMPRESS_SIZE
+    };
+
    // Try system zlib first on macOS (Apple's ARM64-optimized libz is ~1.4x
    // faster at decompression than zlib-ng on Apple Silicon).
    #[cfg(all(target_os = "macos", feature = "system-zlib-decompress"))]
    {
        if let Ok(result) = sysz::decompress(data) {
+            if result.len() > limit {
+                return Err(FormatError::DecompressionError(
+                    "deflate: output exceeds expected chunk size".into(),
+                ));
+            }
            return Ok(result);
        }
        // Fall through to flate2 on error
    }

    use std::io::Read;
-    let mut decoder = flate2::read::ZlibDecoder::new(data);
-    let mut result = Vec::new();
+    let decoder = flate2::read::ZlibDecoder::new(data);
+    let mut result = Vec::with_capacity(limit.min(1 << 20));
+    // Read one byte past the limit so an over-size stream is distinguishable
+    // from one that legitimately ends exactly at the limit.
    decoder
+        .take(limit as u64 + 1)
        .read_to_end(&mut result)
        .map_err(|e| FormatError::DecompressionError(e.to_string()))?;
+    if result.len() > limit {
+        return Err(FormatError::DecompressionError(
+            "deflate: output exceeds size limit".into(),
+        ));
+    }
    Ok(result)
 }

@@ -659,7 +715,7 @@ mod sysz {
 }

 #[cfg(not(feature = "deflate"))]
-fn deflate_decompress(_data: &[u8]) -> Result<Vec<u8>, FormatError> {
+fn deflate_decompress(_data: &[u8], _expected_bytes: usize) -> Result<Vec<u8>, FormatError> {
    Err(FormatError::UnsupportedFilter(FILTER_DEFLATE))
 }

@@ -682,20 +738,35 @@ fn deflate_compress(_data: &[u8], _level: u32) -> Result<Vec<u8>, FormatError> {
 }

 /// Decompress LZ4 data. Format: 4 bytes LE original size + LZ4 block data.
+///
+/// The 4-byte "original size" header is part of the attacker-controlled
+/// compressed payload itself, so it is bounded against `expected_bytes` (the
+/// pipeline's declared chunk size) before being used to size the output
+/// allocation — otherwise a crafted 4-byte value can request up to ~4 GiB.
 #[cfg(feature = "lz4")]
-fn lz4_decompress(data: &[u8]) -> Result<Vec<u8>, FormatError> {
+fn lz4_decompress(data: &[u8], expected_bytes: usize) -> Result<Vec<u8>, FormatError> {
    if data.len() < 4 {
        return Err(FormatError::DecompressionError(
            "lz4: data too short".into(),
        ));
    }
    let orig_size = u32::from_le_bytes([data[0], data[1], data[2], data[3]]) as usize;
+    if expected_bytes != 0 && orig_size > expected_bytes {
+        return Err(FormatError::DecompressionError(
+            "lz4: declared size exceeds chunk size".into(),
+        ));
+    }
+    if orig_size > MAX_DECOMPRESS_SIZE {
+        return Err(FormatError::DecompressionError(
+            "lz4: declared size exceeds limit".into(),
+        ));
+    }
    lz4_flex::block::decompress(&data[4..], orig_size)
        .map_err(|e| FormatError::DecompressionError(format!("lz4: {e}")))
 }

 #[cfg(not(feature = "lz4"))]
-fn lz4_decompress(_data: &[u8]) -> Result<Vec<u8>, FormatError> {
+fn lz4_decompress(_data: &[u8], _expected_bytes: usize) -> Result<Vec<u8>, FormatError> {
    Err(FormatError::UnsupportedFilter(FILTER_LZ4))
 }

@@ -715,13 +786,35 @@ fn lz4_compress(_data: &[u8]) -> Result<Vec<u8>, FormatError> {
 }

 /// Decompress zstd data.
+///
+/// `expected_bytes` bounds the output (or [`MAX_DECOMPRESS_SIZE`] when
+/// unavailable) to guard against a zstd decompression bomb, since zstd's
+/// compression ratio can exceed 1000:1.
 #[cfg(feature = "zstd")]
-fn zstd_decompress(data: &[u8]) -> Result<Vec<u8>, FormatError> {
-    zstd::decode_all(data).map_err(|e| FormatError::DecompressionError(format!("zstd: {e}")))
+fn zstd_decompress(data: &[u8], expected_bytes: usize) -> Result<Vec<u8>, FormatError> {
+    use std::io::Read;
+    let limit = if expected_bytes != 0 {
+        expected_bytes
+    } else {
+        MAX_DECOMPRESS_SIZE
+    };
+    let decoder = zstd::stream::Decoder::new(data)
+        .map_err(|e| FormatError::DecompressionError(format!("zstd: {e}")))?;
+    let mut out = Vec::with_capacity(limit.min(1 << 20));
+    decoder
+        .take(limit as u64 + 1)
+        .read_to_end(&mut out)
+        .map_err(|e| FormatError::DecompressionError(format!("zstd: {e}")))?;
+    if out.len() > limit {
+        return Err(FormatError::DecompressionError(
+            "zstd: output exceeds chunk size".into(),
+        ));
+    }
+    Ok(out)
 }

 #[cfg(not(feature = "zstd"))]
-fn zstd_decompress(_data: &[u8]) -> Result<Vec<u8>, FormatError> {
+fn zstd_decompress(_data: &[u8], _expected_bytes: usize) -> Result<Vec<u8>, FormatError> {
    Err(FormatError::UnsupportedFilter(FILTER_ZSTD))
 }

@@ -982,30 +1075,74 @@ fn pcodec_compress(_data: &[u8], _element_size: usize) -> Result<Vec<u8>, Format
    Err(FormatError::UnsupportedFilter(FILTER_PCODEC))
 }

+/// `expected_bytes` bounds the number of elements decoded: the output buffer
+/// is pre-sized to exactly `expected_bytes / element_size` elements and
+/// `simple_decompress_into` never writes past it, so a corrupted/hostile pco
+/// stream cannot force over-allocation the way an unbounded `simple_decompress`
+/// (which allocates however many elements the stream claims) could.
 #[cfg(feature = "pcodec")]
-fn pcodec_decompress(data: &[u8], element_size: usize) -> Result<Vec<u8>, FormatError> {
-    use pco::standalone::simple_decompress;
+fn pcodec_decompress(
+    data: &[u8],
+    element_size: usize,
+    expected_bytes: usize,
+) -> Result<Vec<u8>, FormatError> {
+    use pco::standalone::simple_decompress_into;
+    let limit_bytes = if expected_bytes != 0 {
+        expected_bytes
+    } else {
+        MAX_DECOMPRESS_SIZE
+    };
+    let n = if element_size != 0 {
+        limit_bytes / element_size
+    } else {
+        0
+    };
    match element_size {
        4 => {
-            let nums = simple_decompress::<f32>(data)
+            let mut buf = vec![0f32; n];
+            let progress = simple_decompress_into(data, &mut buf)
                .map_err(|e| FormatError::DecompressionError(format!("pco: {e}")))?;
-            Ok(nums.iter().flat_map(|x| x.to_le_bytes()).collect())
+            if !progress.finished {
+                return Err(FormatError::DecompressionError(
+                    "pco: stream contains more data than expected chunk size allows".into(),
+                ));
+            }
+            buf.truncate(progress.n_processed);
+            Ok(buf.iter().flat_map(|x| x.to_le_bytes()).collect())
        }
        8 => {
-            let nums = simple_decompress::<f64>(data)
+            let mut buf = vec![0f64; n];
+            let progress = simple_decompress_into(data, &mut buf)
                .map_err(|e| FormatError::DecompressionError(format!("pco: {e}")))?;
-            Ok(nums.iter().flat_map(|x| x.to_le_bytes()).collect())
+            if !progress.finished {
+                return Err(FormatError::DecompressionError(
+                    "pco: stream contains more data than expected chunk size allows".into(),
+                ));
+            }
+            buf.truncate(progress.n_processed);
+            Ok(buf.iter().flat_map(|x| x.to_le_bytes()).collect())
        }
        _ => {
-            let nums = simple_decompress::<u32>(data)
+            let mut buf = vec![0u32; n];
+            let progress = simple_decompress_into(data, &mut buf)
                .map_err(|e| FormatError::DecompressionError(format!("pco: {e}")))?;
-            Ok(nums.iter().flat_map(|x| x.to_le_bytes()).collect())
+            if !progress.finished {
+                return Err(FormatError::DecompressionError(
+                    "pco: stream contains more data than expected chunk size allows".into(),
+                ));
+            }
+            buf.truncate(progress.n_processed);
+            Ok(buf.iter().flat_map(|x| x.to_le_bytes()).collect())
        }
    }
 }

 #[cfg(not(feature = "pcodec"))]
-fn pcodec_decompress(_data: &[u8], _element_size: usize) -> Result<Vec<u8>, FormatError> {
+fn pcodec_decompress(
+    _data: &[u8],
+    _element_size: usize,
+    _expected_bytes: usize,
+) -> Result<Vec<u8>, FormatError> {
    Err(FormatError::UnsupportedFilter(FILTER_PCODEC))
 }

@@ -1021,7 +1158,7 @@ mod tests {
    fn deflate_compress_decompress_roundtrip() {
        let data: Vec<u8> = (0..256).map(|i| (i % 256) as u8).collect();
        let compressed = deflate_compress(&data, 6).unwrap();
-        let decompressed = deflate_decompress(&compressed).unwrap();
+        let decompressed = deflate_decompress(&compressed, data.len()).unwrap();
        assert_eq!(decompressed, data);
    }

@@ -1034,7 +1171,7 @@ mod tests {
        let compressed: Vec<u8> = vec![
            120, 156, 99, 96, 100, 98, 102, 97, 101, 99, 231, 224, 4, 0, 0, 175, 0, 46,
        ];
-        let decompressed = deflate_decompress(&compressed).unwrap();
+        let decompressed = deflate_decompress(&compressed, 10).unwrap();
        assert_eq!(decompressed, vec![0, 1, 2, 3, 4, 5, 6, 7, 8, 9]);
    }

@@ -1045,7 +1182,7 @@ mod tests {
        let data = vec![0u8, 1, 2, 3, 4, 5, 6, 7, 8, 9];
        let compressed = deflate_compress(&data, 6).unwrap();
        assert!(!compressed.is_empty());
-        let decompressed = deflate_decompress(&compressed).unwrap();
+        let decompressed = deflate_decompress(&compressed, data.len()).unwrap();
        assert_eq!(decompressed, data);
    }

@@ -1246,7 +1383,7 @@ mod tests {
    fn lz4_compress_decompress_roundtrip() {
        let data: Vec<u8> = (0..256).map(|i| (i % 256) as u8).collect();
        let compressed = lz4_compress(&data).unwrap();
-        let decompressed = lz4_decompress(&compressed).unwrap();
+        let decompressed = lz4_decompress(&compressed, data.len()).unwrap();
        assert_eq!(decompressed, data);
    }

@@ -1301,7 +1438,7 @@ mod tests {
    fn zstd_compress_decompress_roundtrip() {
        let data: Vec<u8> = (0..256).map(|i| (i % 256) as u8).collect();
        let compressed = zstd_compress(&data, 3).unwrap();
-        let decompressed = zstd_decompress(&compressed).unwrap();
+        let decompressed = zstd_decompress(&compressed, data.len()).unwrap();
        assert_eq!(decompressed, data);
    }

@@ -1372,7 +1509,10 @@ mod tests {
            0x02, 0x00, 0x00, 0x00, 0x08, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
            0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xc6, 0x00,
        ];
-        assert_eq!(scaleoffset_decompress(&raw, &cd, 0).unwrap(), i32_le(&[0, 1, 2, 3]));
+        assert_eq!(
+            scaleoffset_decompress(&raw, &cd, 0).unwrap(),
+            i32_le(&[0, 1, 2, 3])
+        );
    }

    #[test]
@@ -1450,9 +1590,9 @@ mod tests {
        let cd = [1u32, 1, 4, 0, 8, 0, 0, 0];
        let raw: &[u8] = &[
            2, 0, 0, 0, // minbits=2
-            8,          // minval_width=8
+            8, // minval_width=8
            0, 0, 0, 0, 0, 0, 0, 0, // minval=0.0f64
-            0, 0, 0, 0, 0, 0, 0, 0, // 8 reserved bytes
+            0, 0, 0, 0, 0, 0, 0, 0,    // 8 reserved bytes
            0x1B, // packed codes: 00 01 10 11 MSB-first
        ];
        let got = as_f64(&scaleoffset_decompress(raw, &cd, 0).unwrap());
@@ -1466,9 +1606,9 @@ mod tests {
        let cd = [1u32, 0xFFFF_FFFF, 4, 0, 8, 0, 0, 0];
        let raw: &[u8] = &[
            2, 0, 0, 0, // minbits=2
-            8,          // minval_width=8
+            8, // minval_width=8
            0, 0, 0, 0, 0, 0, 0, 0, // minval=0.0f64
-            0, 0, 0, 0, 0, 0, 0, 0, // 8 reserved bytes
+            0, 0, 0, 0, 0, 0, 0, 0,    // 8 reserved bytes
            0x1B, // packed codes: 00 01 10 11 MSB-first
        ];
        let got = as_f64(&scaleoffset_decompress(raw, &cd, 0).unwrap());
@@ -1531,8 +1671,12 @@ mod tests {
    fn nbit_compound_with_array_member() {
        // Compound { a: array(2,) of i32 prec 16 @0; b: u32@8 prec 8 }, 2 elements.
        // data = [([-1,100],200), ([1000,-32768],7)].
-        let cd = [20u32, 0, 2, 3, 12, 2, 0, 2, 8, 1, 4, 0, 16, 0, 8, 1, 4, 0, 8, 0];
-        let raw = [0xff, 0xff, 0x00, 0x64, 0xc8, 0x03, 0xe8, 0x80, 0x00, 0x07, 0x00];
+        let cd = [
+            20u32, 0, 2, 3, 12, 2, 0, 2, 8, 1, 4, 0, 16, 0, 8, 1, 4, 0, 8, 0,
+        ];
+        let raw = [
+            0xff, 0xff, 0x00, 0x64, 0xc8, 0x03, 0xe8, 0x80, 0x00, 0x07, 0x00,
+        ];
        #[rustfmt::skip]
        let expected: Vec<u8> = vec![
            0xff,0xff,0x00,0x00, 0x64,0x00,0x00,0x00, 0xc8,0x00,0x00,0x00, // ([-1,100], 200)
@@ -1623,4 +1767,79 @@ mod tests {
        // Missing client data entirely.
        assert!(scaleoffset_decompress(&[0u8; 32], &[2, 0], 4).is_err());
    }
+
+    // ----- Decompression-bomb hardening: hostile compressed data must not -----
+    // ----- force unbounded allocation.                                    -----
+
+    #[test]
+    #[cfg(feature = "lz4")]
+    fn lz4_decompress_rejects_oversized_orig_size() {
+        // 4-byte LE header claiming ~4 GiB, followed by a few garbage bytes.
+        let mut data = u32::MAX.to_le_bytes().to_vec();
+        data.extend_from_slice(&[0u8; 8]);
+        assert!(lz4_decompress(&data, 64).is_err());
+    }
+
+    #[test]
+    #[cfg(feature = "lz4")]
+    fn lz4_decompress_rejects_size_exceeding_chunk_size() {
+        // orig_size (1000) is well under MAX_DECOMPRESS_SIZE but exceeds the
+        // pipeline's declared chunk size (64) — must be rejected by the
+        // chunk-size check specifically, not just the absolute cap.
+        let mut data = 1000u32.to_le_bytes().to_vec();
+        data.extend_from_slice(&[0u8; 8]);
+        assert!(lz4_decompress(&data, 64).is_err());
+    }
+
+    #[test]
+    #[cfg(feature = "deflate")]
+    fn deflate_decompress_rejects_output_exceeding_chunk_size() {
+        // A highly-compressible deflate bomb (1 MiB of zeros compresses to a
+        // tiny payload); declared chunk size is far smaller than the real
+        // decompressed size, so this must be rejected rather than allocating
+        // the full 1 MiB.
+        let data = vec![0u8; 1024 * 1024];
+        let compressed = deflate_compress(&data, 6).unwrap();
+        assert!(deflate_decompress(&compressed, 64).is_err());
+    }
+
+    #[test]
+    #[cfg(feature = "zstd")]
+    fn zstd_decompress_rejects_output_exceeding_chunk_size() {
+        let data = vec![0u8; 1024 * 1024];
+        let compressed = zstd_compress(&data, 3).unwrap();
+        assert!(zstd_decompress(&compressed, 64).is_err());
+    }
+
+    #[test]
+    #[cfg(feature = "pcodec")]
+    fn pcodec_decompress_rejects_element_count_exceeding_chunk_size() {
+        let data: Vec<f32> = (0..1000).map(|i| i as f32).collect();
+        let raw: Vec<u8> = data.iter().flat_map(|x| x.to_le_bytes()).collect();
+        let compressed = pcodec_compress(&raw, 4).unwrap();
+        // Declared chunk size only fits 4 f32 elements, far fewer than the
+        // 1000 the stream actually contains.
+        assert!(pcodec_decompress(&compressed, 4, 16).is_err());
+    }
+
+    #[test]
+    #[cfg(feature = "lz4")]
+    fn decompress_chunk_rejects_hostile_lz4_size_via_public_entrypoint() {
+        // The actually-exploited path: a FilterPipeline claiming a small
+        // chunk_size, but whose LZ4-compressed data header claims a huge
+        // decompressed size.
+        use crate::filter_pipeline::{FilterDescription, FilterPipeline};
+        let mut data = u32::MAX.to_le_bytes().to_vec();
+        data.extend_from_slice(&[0u8; 8]);
+        let pipeline = FilterPipeline {
+            version: 2,
+            filters: vec![FilterDescription {
+                filter_id: FILTER_LZ4,
+                name: None,
+                flags: 0,
+                client_data: vec![],
+            }],
+        };
+        assert!(decompress_chunk(&data, &pipeline, 16, 1).is_err());
+    }
 }
@@ -2,6 +2,9 @@
 //!
 //! Gated by the `szip` feature which links against the system libaec library.

+#[cfg(not(feature = "std"))]
+use alloc::vec::Vec;
+
 use crate::error::FormatError;

 /// Decompress SZIP-compressed data using libaec.
@@ -49,9 +52,7 @@ fn szip_decode_impl(data: &[u8], cd: &[u32], chunk_size: usize) -> Result<Vec<u8
        ));
    }
    if data.is_empty() {
-        return Err(FormatError::ChunkedReadError(
-            "szip: empty input".into(),
-        ));
+        return Err(FormatError::ChunkedReadError("szip: empty input".into()));
    }

    // Map HDF5 option mask to libaec flags.
@@ -112,7 +113,7 @@ mod tests {
    #[cfg(feature = "szip")]
    #[test]
    fn roundtrip_u8_msb_no_nn() {
-        use libaec_sys::{AecStream, AEC_DATA_MSB};
+        use libaec_sys::{AEC_DATA_MSB, AecStream};

        let original: Vec<u8> = (0..1024u32).map(|i| (i % 256) as u8).collect();

@@ -144,7 +145,7 @@ mod tests {
    #[cfg(feature = "szip")]
    #[test]
    fn roundtrip_u8_msb_with_nn() {
-        use libaec_sys::{AecStream, AEC_DATA_MSB, AEC_DATA_PREPROCESS};
+        use libaec_sys::{AEC_DATA_MSB, AEC_DATA_PREPROCESS, AecStream};

        let original: Vec<u8> = (0..1024u32).map(|i| (i % 256) as u8).collect();

@@ -167,6 +168,9 @@ mod tests {
        let cd = [0x20u32, 8, 8, 1024];
        let decoded = szip_decompress(&encoded, &cd, original.len())
            .expect("szip_decompress with NN must succeed");
-        assert_eq!(decoded, original, "NN round-trip must reproduce original data");
+        assert_eq!(
+            decoded, original,
+            "NN round-trip must reproduce original data"
+        );
    }
 }
@@ -186,25 +186,26 @@ pub fn read_fixed_array_chunks(
        chunk_dimensions.iter().map(|&d| d as u64).product::<u64>() * element_size as u64;

    let mut chunks = Vec::new();
-    let push_element = |i: usize, abs: usize, chunks: &mut Vec<ChunkInfo>| -> Result<(), FormatError> {
-        if let Some((address, chunk_size, filter_mask)) = parse_fa_element(
-            file_data,
-            abs,
-            header.client_id,
-            offset_size,
-            header.element_size,
-            chunk_byte_size,
-        )? {
-            let offsets = index_to_chunk_offsets(i, &num_chunks_per_dim, chunk_dimensions);
-            chunks.push(ChunkInfo {
-                chunk_size,
-                filter_mask,
-                offsets,
-                address,
-            });
-        }
-        Ok(())
-    };
+    let push_element =
+        |i: usize, abs: usize, chunks: &mut Vec<ChunkInfo>| -> Result<(), FormatError> {
+            if let Some((address, chunk_size, filter_mask)) = parse_fa_element(
+                file_data,
+                abs,
+                header.client_id,
+                offset_size,
+                header.element_size,
+                chunk_byte_size,
+            )? {
+                let offsets = index_to_chunk_offsets(i, &num_chunks_per_dim, chunk_dimensions);
+                chunks.push(ChunkInfo {
+                    chunk_size,
+                    filter_mask,
+                    offsets,
+                    address,
+                });
+            }
+            Ok(())
+        };

    // A data block is paged when it holds more elements than fit in one page.
    // `max_nelmts_bits` is an untrusted u8; a shift >= the pointer width would
@@ -232,9 +233,8 @@ pub fn read_fixed_array_chunks(
    // only the final page holds fewer elements. Uninitialized pages (bit clear)
    // still occupy their slot on disk but are zero-filled, so the bitmap — not a
    // 0xFF sentinel — is what marks a whole page as unallocated.
-    let stride_overflow = || {
-        FormatError::ChunkedReadError("Fixed Array page offset overflow".into())
-    };
+    let stride_overflow =
+        || FormatError::ChunkedReadError("Fixed Array page offset overflow".into());
    let npages = num_elements.div_ceil(page_nelmts);
    let bitmap_size = npages.div_ceil(8);
    let bitmap_start = elements_start;
@@ -720,10 +720,7 @@ mod tests {
        // Page 1 (elements 4,5,6,7) is uninitialized => skipped. The remaining
        // 7 chunks (0..4 and 8..11) come back with their original linear index.
        assert_eq!(chunks.len(), 7);
-        let mut got: Vec<(u64, u64)> = chunks
-            .iter()
-            .map(|c| (c.offsets[0], c.address))
-            .collect();
+        let mut got: Vec<(u64, u64)> = chunks.iter().map(|c| (c.offsets[0], c.address)).collect();
        got.sort();
        let expect: Vec<(u64, u64)> = [0usize, 1, 2, 3, 8, 9, 10]
            .iter()
@@ -6,7 +6,7 @@ use alloc::vec::Vec;
 use crate::error::FormatError;

 /// Magic signature for global heap collections.
-const GCOL_SIGNATURE: [u8; 4] = [b'G', b'C', b'O', b'L'];
+const GCOL_SIGNATURE: [u8; 4] = *b"GCOL";

 /// A parsed global heap collection.
 #[derive(Debug, Clone)]
@@ -16,6 +16,21 @@ pub struct LocalHeap {
    pub data_segment_address: u64,
 }

+/// Checks that `[offset, offset + needed)` fits within `data`, guarding the
+/// addition against `usize` overflow from a crafted near-`usize::MAX` offset.
+fn ensure_len(data: &[u8], offset: usize, needed: usize) -> Result<(), FormatError> {
+    if offset
+        .checked_add(needed)
+        .is_none_or(|end| end > data.len())
+    {
+        return Err(FormatError::UnexpectedEof {
+            expected: offset.saturating_add(needed),
+            available: data.len(),
+        });
+    }
+    Ok(())
+}
+
 fn read_offset(data: &[u8], pos: usize, size: u8) -> Result<u64, FormatError> {
    let s = size as usize;
    if pos.checked_add(s).is_none_or(|end| end > data.len()) {
@@ -47,12 +62,7 @@ impl LocalHeap {
        let ls = length_size as usize;
        let os = offset_size as usize;
        let total = 8 + ls * 2 + os;
-        if offset + total > file_data.len() {
-            return Err(FormatError::UnexpectedEof {
-                expected: offset + total,
-                available: file_data.len(),
-            });
-        }
+        ensure_len(file_data, offset, total)?;

        if &file_data[offset..offset + 4] != b"HEAP" {
            return Err(FormatError::InvalidLocalHeapSignature);
@@ -172,6 +182,18 @@ mod tests {
        }
    }

+    #[test]
+    fn parse_rejects_near_usize_max_offset_without_panicking() {
+        // Found by fuzzing: `offset + total` overflowed for a crafted
+        // near-usize::MAX offset.
+        let file = build_heap_file(0, 100, &["hello"], 8, 8);
+        let result = LocalHeap::parse(&file, usize::MAX - 4, 8, 8);
+        assert!(
+            matches!(result, Err(FormatError::UnexpectedEof { .. })),
+            "expected a clean UnexpectedEof, got {result:?}"
+        );
+    }
+
    #[test]
    fn parse_heap_header() {
        let file = build_heap_file(0, 100, &["hello", "world"], 8, 8);
@@ -9,10 +9,10 @@ use crate::error::FormatError;
 use crate::message_type::MessageType;

 /// OHDR signature for v2 object headers.
-const OHDR_SIGNATURE: [u8; 4] = [b'O', b'H', b'D', b'R'];
+const OHDR_SIGNATURE: [u8; 4] = *b"OHDR";

 /// OCHK signature for v2 continuation chunks.
-const OCHK_SIGNATURE: [u8; 4] = [b'O', b'C', b'H', b'K'];
+const OCHK_SIGNATURE: [u8; 4] = *b"OCHK";

 /// A single parsed header message.
 #[derive(Debug, Clone)]
@@ -555,13 +555,12 @@ mod tests {
        buf.push(2); // version
        buf.push(flags);

-        if has_timestamps
-            && let Some((at, mt, ct, bt)) = timestamps {
-                buf.extend_from_slice(&at.to_le_bytes());
-                buf.extend_from_slice(&mt.to_le_bytes());
-                buf.extend_from_slice(&ct.to_le_bytes());
-                buf.extend_from_slice(&bt.to_le_bytes());
-            }
+        if has_timestamps && let Some((at, mt, ct, bt)) = timestamps {
+            buf.extend_from_slice(&at.to_le_bytes());
+            buf.extend_from_slice(&mt.to_le_bytes());
+            buf.extend_from_slice(&ct.to_le_bytes());
+            buf.extend_from_slice(&bt.to_le_bytes());
+        }

        if flags & 0x10 != 0 {
            buf.extend_from_slice(&8u16.to_le_bytes()); // max_compact
@@ -4,7 +4,7 @@
 //! events. The [`DefaultProfiler`] implementation uses atomic counters for
 //! thread-safe, low-overhead profiling.

-use core::sync::atomic::{AtomicU64, Ordering};
+use portable_atomic::{AtomicU64, Ordering};

 /// Trait for profiling I/O operations.
 ///
@@ -2,6 +2,9 @@
 //! data-integrity verification.
 //!
 //! Enable with the `provenance` Cargo feature (on by default).
+//!
+//! The hash is unkeyed, so this detects accidental corruption only — it is
+//! not a tamper-evidence or authenticity guarantee. See [`verify_dataset`].

 #[cfg(not(feature = "std"))]
 use alloc::{format, string::String, vec::Vec};
@@ -115,6 +118,11 @@ pub enum VerifyResult {
 ///
 /// `file_data` is the entire HDF5 file bytes; `header` is the parsed object
 /// header for the dataset of interest.
+///
+/// This only detects *accidental* corruption. The hash is unkeyed and stored
+/// alongside the data it protects, so anyone able to modify the dataset can
+/// also recompute and overwrite `_provenance_sha256` — a `VerifyResult::Ok`
+/// is not a tamper-evidence or authenticity guarantee.
 pub fn verify_dataset(
    file_data: &[u8],
    header: &ObjectHeader,
@@ -587,7 +587,7 @@ mod tests {
        // start=0 stride=1 count=1 block=4, version 3, enc_size 2, rank 1.
        let bytes = [
            0x02, 0, 0, 0, // type = HYPER
-            0x03, 0, 0, 0, // version 3
+            0x03, 0, 0, 0,    // version 3
            0x01, // flags = regular
            0x02, // enc_size = 2
            0x01, 0, 0, 0, // rank = 1
@@ -90,6 +90,16 @@ pub fn make_i64_type() -> Datatype {
    }
 }

+pub fn make_u64_type() -> Datatype {
+    Datatype::FixedPoint {
+        size: 8,
+        byte_order: DatatypeByteOrder::LittleEndian,
+        signed: false,
+        bit_offset: 0,
+        bit_precision: 64,
+    }
+}
+
 pub fn make_u8_type() -> Datatype {
    Datatype::FixedPoint {
        size: 1,
@@ -444,6 +454,25 @@ impl DatasetBuilder {
        self
    }

+    /// Write a native unsigned 64-bit integer dataset. Pairs with the
+    /// read side's `read_u64`/`read_as_u64`, which already support this
+    /// datatype — this was the missing symmetric write-side builder
+    /// (callers previously had to bit-cast through `with_i64_data` /
+    /// `i64::from_ne_bytes(v.to_ne_bytes())` to round-trip full-range u64
+    /// values like timestamps or IDs).
+    pub fn with_u64_data(&mut self, data: &[u64]) -> &mut Self {
+        self.datatype = Some(make_u64_type());
+        let mut b = Vec::with_capacity(data.len() * 8);
+        for &v in data {
+            b.extend_from_slice(&v.to_le_bytes());
+        }
+        self.data = Some(b);
+        if self.shape.is_none() {
+            self.shape = Some(vec![data.len() as u64]);
+        }
+        self
+    }
+
    pub fn with_u8_data(&mut self, data: &[u8]) -> &mut Self {
        self.datatype = Some(make_u8_type());
        self.data = Some(data.to_vec());
@@ -321,9 +321,9 @@ fn roundtrip_through_file_writer() {
                && let clawhdf5_format::link_message::LinkTarget::Hard {
                    object_header_address,
                } = link.link_target
-                {
-                    ds_addr = Some(object_header_address);
-                }
+            {
+                ds_addr = Some(object_header_address);
+            }
        }
    }
    let ds_addr = ds_addr.expect("compound_ds link not found");
@@ -706,7 +706,10 @@ fn scaleoffset_float_escale_reads_as_raw() {
    let (raw, datatype, _) = read_chunked_dataset(file_data, "x");
    let values = read_as_f64(&raw, &datatype).unwrap();
    let expect: Vec<f64> = (0..20).map(|i| i as f64 * 0.25).collect();
-    assert_eq!(values, expect, "E-scale (raw + masked filter) must read verbatim");
+    assert_eq!(
+        values, expect,
+        "E-scale (raw + masked filter) must read verbatim"
+    );
 }

 #[test]
@@ -717,26 +720,48 @@ fn v4_virtual_dataset_cycle_errors_not_overflow() {
    let offset = find_signature(file_data).unwrap();
    let sb = Superblock::parse(file_data, offset).unwrap();
    let addr = resolve_path_any(file_data, &sb, "virt").unwrap();
-    let hdr = ObjectHeader::parse(file_data, addr as usize, sb.offset_size, sb.length_size).unwrap();
+    let hdr =
+        ObjectHeader::parse(file_data, addr as usize, sb.offset_size, sb.length_size).unwrap();
    let ds = Dataspace::parse(
-        &hdr.messages.iter().find(|m| m.msg_type == MessageType::Dataspace).unwrap().data,
+        &hdr.messages
+            .iter()
+            .find(|m| m.msg_type == MessageType::Dataspace)
+            .unwrap()
+            .data,
        sb.length_size,
    )
    .unwrap();
    let (dt, _) = Datatype::parse(
-        &hdr.messages.iter().find(|m| m.msg_type == MessageType::Datatype).unwrap().data,
+        &hdr.messages
+            .iter()
+            .find(|m| m.msg_type == MessageType::Datatype)
+            .unwrap()
+            .data,
    )
    .unwrap();
    let layout = DataLayout::parse(
-        &hdr.messages.iter().find(|m| m.msg_type == MessageType::DataLayout).unwrap().data,
+        &hdr.messages
+            .iter()
+            .find(|m| m.msg_type == MessageType::DataLayout)
+            .unwrap()
+            .data,
        sb.offset_size,
        sb.length_size,
    )
    .unwrap();
    let r = read_raw_data_full(
-        file_data, &layout, &ds, &dt, None, sb.offset_size, sb.length_size,
+        file_data,
+        &layout,
+        &ds,
+        &dt,
+        None,
+        sb.offset_size,
+        sb.length_size,
+    );
+    assert!(
+        r.is_err(),
+        "cyclic virtual dataset must error, not overflow"
    );
-    assert!(r.is_err(), "cyclic virtual dataset must error, not overflow");
 }

 #[test]
@@ -751,16 +776,28 @@ fn v4_virtual_dataset_external_file_read() {
    let addr = resolve_path_any(virt, &sb, "virt").unwrap();
    let hdr = ObjectHeader::parse(virt, addr as usize, sb.offset_size, sb.length_size).unwrap();
    let ds = Dataspace::parse(
-        &hdr.messages.iter().find(|m| m.msg_type == MessageType::Dataspace).unwrap().data,
+        &hdr.messages
+            .iter()
+            .find(|m| m.msg_type == MessageType::Dataspace)
+            .unwrap()
+            .data,
        sb.length_size,
    )
    .unwrap();
    let (dt, _) = Datatype::parse(
-        &hdr.messages.iter().find(|m| m.msg_type == MessageType::Datatype).unwrap().data,
+        &hdr.messages
+            .iter()
+            .find(|m| m.msg_type == MessageType::Datatype)
+            .unwrap()
+            .data,
    )
    .unwrap();
    let layout = DataLayout::parse(
-        &hdr.messages.iter().find(|m| m.msg_type == MessageType::DataLayout).unwrap().data,
+        &hdr.messages
+            .iter()
+            .find(|m| m.msg_type == MessageType::DataLayout)
+            .unwrap()
+            .data,
        sb.offset_size,
        sb.length_size,
    )
@@ -790,7 +827,14 @@ fn v4_virtual_dataset_external_file_read() {

    // With no resolver, an external source is a clean error (not wrong data).
    let no_resolver = read_raw_data_full_with_resolver(
-        virt, &layout, &ds, &dt, None, sb.offset_size, sb.length_size, None,
+        virt,
+        &layout,
+        &ds,
+        &dt,
+        None,
+        sb.offset_size,
+        sb.length_size,
+        None,
    );
    assert!(no_resolver.is_err());
 }
@@ -805,9 +849,18 @@ fn v4_paged_fixed_array_read() {
    let values = read_as_i32(&raw, &datatype).unwrap();
    assert_eq!(values.len(), 1025 * 16);
    for k in 0..1025usize {
-        assert_eq!(values[k * 16], k as i32, "chunk-start mismatch at chunk {k}");
+        assert_eq!(
+            values[k * 16],
+            k as i32,
+            "chunk-start mismatch at chunk {k}"
+        );
        for j in 1..16 {
-            assert_eq!(values[k * 16 + j], 0, "non-start element nonzero at {}", k * 16 + j);
+            assert_eq!(
+                values[k * 16 + j],
+                0,
+                "non-start element nonzero at {}",
+                k * 16 + j
+            );
        }
    }
 }
@@ -214,9 +214,9 @@ print('ok')
                && let clawhdf5_format::link_message::LinkTarget::Hard {
                    object_header_address,
                } = link.link_target
-                {
-                    refs_addr = Some(object_header_address);
-                }
+            {
+                refs_addr = Some(object_header_address);
+            }
        }
    }

@@ -11,14 +11,14 @@ categories = ["science", "graphics"]

 [dependencies]
 wgpu = { version = "28", optional = true }
-half = { version = "2.7", optional = true }
+half = { workspace = true, optional = true }
 pollster = { version = "0.4", optional = true }
 bytemuck = { version = "1", features = ["derive"], optional = true }
 thiserror = "2"
 log = "0.4"

 [dev-dependencies]
-criterion = { version = "0.5", features = ["html_reports"] }
+criterion = { workspace = true }
 rand = "0.8"
 approx = "0.5"
 pollster = "0.4"
@@ -15,13 +15,13 @@ memmap2 = { version = "0.9", optional = true }
 libc = { version = "0.2", optional = true }
 tokio = { version = "1", features = ["fs", "io-util"], optional = true }
 reqwest = { version = "0.12", features = ["json"], optional = true }
-serde = { version = "1", features = ["derive"], optional = true }
+serde = { workspace = true, optional = true }
 serde_json = { version = "1", optional = true }
 mpi = { version = "0.8", optional = true }

 [dev-dependencies]
 tokio = { version = "1", features = ["full"] }
-tempfile = "3"
+tempfile = { workspace = true }

 [features]
 default = []
@@ -19,7 +19,7 @@ clawhdf5-format = { path = "../clawhdf5-format", version = "2.1.0" }
 clawhdf5 = { path = "../clawhdf5", version = "2.1.0" }
 rusqlite = { version = "0.31", features = ["bundled"] }
 clap = { version = "4", features = ["derive"] }
-half = "2"
+half = { workspace = true }

 [dev-dependencies]
-tempfile = "3"
+tempfile = { workspace = true }
@@ -309,7 +309,8 @@ mod tests {
        insert_relation(&conn, 1, 1, "self");
        drop(conn);

-        let data = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        let opts = hdf5_writer::WriteOptions {
            agent_id: "test-agent".into(),
            embedder: "test-embed".into(),
@@ -319,7 +320,8 @@ mod tests {
        };
        hdf5_writer::write_hdf5(h5_path.to_str().unwrap(), &data, &opts).unwrap();

-        let summary = validate::validate_hdf5(h5_path.to_str().unwrap(), &data, false, false).unwrap();
+        let summary =
+            validate::validate_hdf5(h5_path.to_str().unwrap(), &data, false, false).unwrap();
        assert_eq!(summary.chunks, 2);
        assert_eq!(summary.sessions, 1);
        assert_eq!(summary.entities, 1);
@@ -340,7 +342,8 @@ mod tests {
        insert_chunk(&conn, 3, "also active", &make_embedding(4, 3.0), 0);
        drop(conn);

-        let data = sqlite_reader::read_sqlite(&db_path, true, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, true, None, &SchemaConfig::default()).unwrap();
        assert_eq!(data.chunks.len(), 2);

        let opts = hdf5_writer::WriteOptions {
@@ -352,7 +355,8 @@ mod tests {
        };
        hdf5_writer::write_hdf5(h5_path.to_str().unwrap(), &data, &opts).unwrap();

-        let summary = validate::validate_hdf5(h5_path.to_str().unwrap(), &data, false, false).unwrap();
+        let summary =
+            validate::validate_hdf5(h5_path.to_str().unwrap(), &data, false, false).unwrap();
        assert_eq!(summary.chunks, 2);
    }

@@ -367,7 +371,8 @@ mod tests {
        insert_chunk(&conn, 2, "deleted", &make_embedding(4, 2.0), 1);
        drop(conn);

-        let data = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        assert_eq!(data.chunks.len(), 2);
    }

@@ -381,7 +386,8 @@ mod tests {
        insert_chunk(&conn, 1, "test", &make_embedding(16, 0.5), 0);
        drop(conn);

-        let data = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        assert_eq!(data.embedding_dim, 16);
    }

@@ -395,7 +401,8 @@ mod tests {
        insert_chunk(&conn, 1, "test", &make_embedding(16, 0.5), 0);
        drop(conn);

-        let data = sqlite_reader::read_sqlite(&db_path, false, Some(8), &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, false, Some(8), &SchemaConfig::default()).unwrap();
        assert_eq!(data.embedding_dim, 8);
        // Embedding truncated to dim 8
        assert_eq!(data.chunks[0].embedding.len(), 8);
@@ -413,7 +420,8 @@ mod tests {
        insert_chunk(&conn, 1, "test", &emb, 0);
        drop(conn);

-        let data = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        let opts = hdf5_writer::WriteOptions {
            agent_id: "t".into(),
            embedder: "t".into(),
@@ -424,7 +432,8 @@ mod tests {
        hdf5_writer::write_hdf5(h5_path.to_str().unwrap(), &data, &opts).unwrap();

        // Content-validate with the float16 tolerance enabled.
-        let summary = validate::validate_hdf5(h5_path.to_str().unwrap(), &data, true, true).unwrap();
+        let summary =
+            validate::validate_hdf5(h5_path.to_str().unwrap(), &data, true, true).unwrap();
        assert_eq!(summary.chunks, 1);

        // Verify float16 values are within tolerance
@@ -453,7 +462,8 @@ mod tests {
        }
        drop(conn);

-        let data = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();

        let opts_compressed = hdf5_writer::WriteOptions {
            agent_id: "t".into(),
@@ -493,7 +503,8 @@ mod tests {
        drop(conn);

        // Simulate dry-run: read data but don't write
-        let data = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        assert_eq!(data.chunks.len(), 1);
        assert!(!h5_path.exists());
    }
@@ -505,7 +516,8 @@ mod tests {
        let db_path = create_test_db(&dir);
        let h5_path = dir.path().join("out.h5");

-        let data = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        assert_eq!(data.chunks.len(), 0);
        assert_eq!(data.sessions.len(), 0);
        assert_eq!(data.entities.len(), 0);
@@ -520,7 +532,8 @@ mod tests {
        };
        hdf5_writer::write_hdf5(h5_path.to_str().unwrap(), &data, &opts).unwrap();

-        let summary = validate::validate_hdf5(h5_path.to_str().unwrap(), &data, false, false).unwrap();
+        let summary =
+            validate::validate_hdf5(h5_path.to_str().unwrap(), &data, false, false).unwrap();
        assert_eq!(summary.chunks, 0);
    }

@@ -543,7 +556,8 @@ mod tests {
        }
        drop(conn);

-        let data = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        assert_eq!(data.chunks.len(), 1000);

        let opts = hdf5_writer::WriteOptions {
@@ -573,7 +587,8 @@ mod tests {
        insert_session(&conn, "session-gamma", 21, 30);
        drop(conn);

-        let data = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        assert_eq!(data.sessions.len(), 3);

        let opts = hdf5_writer::WriteOptions {
@@ -585,7 +600,8 @@ mod tests {
        };
        hdf5_writer::write_hdf5(h5_path.to_str().unwrap(), &data, &opts).unwrap();

-        let summary = validate::validate_hdf5(h5_path.to_str().unwrap(), &data, false, false).unwrap();
+        let summary =
+            validate::validate_hdf5(h5_path.to_str().unwrap(), &data, false, false).unwrap();
        assert_eq!(summary.sessions, 3);
    }

@@ -605,7 +621,8 @@ mod tests {
        insert_relation(&conn, 2, 3, "uses");
        drop(conn);

-        let data = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        assert_eq!(data.entities.len(), 3);
        assert_eq!(data.relations.len(), 3);

@@ -618,7 +635,8 @@ mod tests {
        };
        hdf5_writer::write_hdf5(h5_path.to_str().unwrap(), &data, &opts).unwrap();

-        let summary = validate::validate_hdf5(h5_path.to_str().unwrap(), &data, false, false).unwrap();
+        let summary =
+            validate::validate_hdf5(h5_path.to_str().unwrap(), &data, false, false).unwrap();
        assert_eq!(summary.entities, 3);
        assert_eq!(summary.relations, 3);
    }
@@ -634,7 +652,8 @@ mod tests {
        insert_chunk(&conn, 1, "test", &make_embedding(4, 1.0), 0);
        drop(conn);

-        let data = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        let opts = hdf5_writer::WriteOptions {
            agent_id: "t".into(),
            embedder: "t".into(),
@@ -645,8 +664,8 @@ mod tests {
        hdf5_writer::write_hdf5(h5_path.to_str().unwrap(), &data, &opts).unwrap();

        // Validating against a source with an extra (unwritten) chunk must fail.
-        let mut bigger = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default())
-            .unwrap();
+        let mut bigger =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        let mut extra = bigger.chunks[0].clone();
        extra.id = 999;
        bigger.chunks.push(extra);
@@ -666,7 +685,8 @@ mod tests {
        insert_chunk(&conn, 1, "test", &make_embedding(8, 1.0), 0);
        drop(conn);

-        let data = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        let opts = hdf5_writer::WriteOptions {
            agent_id: "my-agent-42".into(),
            embedder: "openai-ada".into(),
@@ -712,7 +732,8 @@ mod tests {
        insert_chunk(&conn, 1, "test", &emb, 0);
        drop(conn);

-        let data = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        let opts = hdf5_writer::WriteOptions {
            agent_id: "t".into(),
            embedder: "t".into(),
@@ -758,7 +779,8 @@ mod tests {
        drop(conn);

        // Skip deleted
-        let data = sqlite_reader::read_sqlite(&db_path, true, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, true, None, &SchemaConfig::default()).unwrap();
        assert_eq!(data.chunks.len(), 4); // chunk 3 is deleted

        let opts = hdf5_writer::WriteOptions {
@@ -770,7 +792,8 @@ mod tests {
        };
        hdf5_writer::write_hdf5(h5_path.to_str().unwrap(), &data, &opts).unwrap();

-        let summary = validate::validate_hdf5(h5_path.to_str().unwrap(), &data, false, false).unwrap();
+        let summary =
+            validate::validate_hdf5(h5_path.to_str().unwrap(), &data, false, false).unwrap();
        assert_eq!(summary.chunks, 4);
        assert_eq!(summary.sessions, 2);
        assert_eq!(summary.entities, 2);
@@ -789,7 +812,8 @@ mod tests {
        insert_session(&conn, "s1", 0, 10);
        drop(conn);

-        let data = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        let opts = hdf5_writer::WriteOptions {
            agent_id: "t".into(),
            embedder: "t".into(),
@@ -800,8 +824,8 @@ mod tests {
        hdf5_writer::write_hdf5(h5_path.to_str().unwrap(), &data, &opts).unwrap();

        // Validating against a source whose session content differs must fail.
-        let mut tampered = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default())
-            .unwrap();
+        let mut tampered =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        tampered.sessions[0].summary = "DIFFERENT".into();
        let result = validate::validate_hdf5(h5_path.to_str().unwrap(), &tampered, false, false);
        assert!(result.is_err());
@@ -819,7 +843,8 @@ mod tests {
        insert_chunk(&conn, 1, "hello", &make_embedding(8, 1.0), 0);
        drop(conn);

-        let data = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
+        let data =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        let opts = hdf5_writer::WriteOptions {
            agent_id: "t".into(),
            embedder: "t".into(),
@@ -830,8 +855,8 @@ mod tests {
        hdf5_writer::write_hdf5(h5_path.to_str().unwrap(), &data, &opts).unwrap();

        // A source whose embedding differs (but counts match) must fail validation.
-        let mut tampered = sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default())
-            .unwrap();
+        let mut tampered =
+            sqlite_reader::read_sqlite(&db_path, false, None, &SchemaConfig::default()).unwrap();
        tampered.chunks[0].embedding[3] += 9.0;
        let result = validate::validate_hdf5(h5_path.to_str().unwrap(), &tampered, true, false);
        assert!(result.is_err());
@@ -856,7 +881,10 @@ mod tests {
            CREATE TABLE relations (src INTEGER, tgt INTEGER, relation TEXT, weight REAL, timestamp REAL);",
        )
        .unwrap();
-        let blob: Vec<u8> = make_embedding(4, 1.0).iter().flat_map(|v| v.to_le_bytes()).collect();
+        let blob: Vec<u8> = make_embedding(4, 1.0)
+            .iter()
+            .flat_map(|v| v.to_le_bytes())
+            .collect();
        conn.execute(
            "INSERT INTO my_chunks VALUES (1, 'hi', ?1, 'api', 1.0, 's', '', 0)",
            rusqlite::params![blob],
@@ -908,7 +936,8 @@ mod tests {
        let base = hdf5_reader::read_hdf5(h5_path.to_str().unwrap()).unwrap();
        let max_id = base.chunks.iter().map(|c| c.id).max().unwrap_or(0);
        assert_eq!(max_id, 2);
-        let new = sqlite_reader::read_sqlite_filtered(&db_path, false, Some(4), &cfg, max_id).unwrap();
+        let new =
+            sqlite_reader::read_sqlite_filtered(&db_path, false, Some(4), &cfg, max_id).unwrap();
        assert_eq!(new.chunks.len(), 2); // only id 3 and 4

        let mut merged = base;
@@ -91,7 +91,14 @@ impl Default for SchemaConfig {
            },
            sessions: TableSchema {
                table: "sessions".into(),
-                columns: vec!["id", "start_idx", "end_idx", "channel", "timestamp", "summary"],
+                columns: vec![
+                    "id",
+                    "start_idx",
+                    "end_idx",
+                    "channel",
+                    "timestamp",
+                    "summary",
+                ],
            },
            entities: TableSchema {
                table: "entities".into(),
@@ -77,10 +77,9 @@ pub fn validate_hdf5(
        }
        for (k, (&a, &b)) in s.embedding.iter().zip(g.embedding.iter()).enumerate() {
            if (a - b).abs() > emb_abs + emb_rel * a.abs() {
-                return Err(format!(
-                    "chunk[{i}].embedding[{k}] mismatch: source {a}, HDF5 {b}"
-                )
-                .into());
+                return Err(
+                    format!("chunk[{i}].embedding[{k}] mismatch: source {a}, HDF5 {b}").into(),
+                );
            }
        }
        rows_checked += 1;
@@ -108,7 +107,12 @@ pub fn validate_hdf5(
        }
        rows_checked += 1;
    }
-    for (i, (s, g)) in source.relations.iter().zip(got.relations.iter()).enumerate() {
+    for (i, (s, g)) in source
+        .relations
+        .iter()
+        .zip(got.relations.iter())
+        .enumerate()
+    {
        if s.src != g.src || s.tgt != g.tgt || s.relation != g.relation {
            return Err(format!("relation[{i}] mismatch").into());
        }
@@ -14,4 +14,4 @@ clawhdf5 = { path = "../clawhdf5", version = "2.1.0" }
 clawhdf5-format = { path = "../clawhdf5-format", version = "2.1.0" }

 [dev-dependencies]
-tempfile = "3"
+tempfile = { workspace = true }
@@ -16,8 +16,8 @@ crate-type = ["cdylib", "rlib"]
 [dependencies]
 clawhdf5_rs = { path = "../clawhdf5", version = "2.1.0", package = "clawhdf5" }
 clawhdf5-format = { path = "../clawhdf5-format", version = "2.1.0" }
-pyo3 = "0.28"
-numpy = "0.28"
+pyo3 = "0.29"
+numpy = "0.29"

 [features]
 extension-module = ["pyo3/extension-module"]
@@ -4,7 +4,7 @@ build-backend = "maturin"

 [project]
 name = "rustyhdf5"
-version = "1.93.0"
+version = "2.1.0"
 description = "Python bindings for rustyhdf5 — a pure-Rust HDF5 library"
 requires-python = ">=3.8"
 license = { text = "MIT" }
@@ -15,8 +15,8 @@ clawhdf5-io = { path = "../clawhdf5-io", version = "2.1.0" }
 rayon = { version = "1", optional = true }

 [dev-dependencies]
-tempfile = "3"
-criterion = { version = "0.5", features = ["html_reports"] }
+tempfile = { workspace = true }
+criterion = { workspace = true }
 clawhdf5-io = { path = "../clawhdf5-io", version = "2.1.0", features = ["mmap"] }
 clawhdf5-format = { path = "../clawhdf5-format", version = "2.1.0", features = ["parallel", "fast-checksum"] }
 clawhdf5-filters = { path = "../clawhdf5-filters", version = "2.1.0" }
@@ -30,7 +30,7 @@ name = "parallel_bench"
 harness = false

 [features]
-default = ["mmap", "fast-deflate"]
+default = ["mmap"]
 mmap = ["clawhdf5-io/mmap"]
 parallel = ["clawhdf5-format/parallel", "rayon"]
 fast-deflate = ["clawhdf5-format/fast-deflate"]
@@ -494,7 +494,9 @@ mod tests {
        let file = File::open(&path).unwrap();
        let ds = file.dataset("data").unwrap();

-        if let Ok(slice) = ds.read_f32_zerocopy() { assert_eq!(slice, &original[..]) }
+        if let Ok(slice) = ds.read_f32_zerocopy() {
+            assert_eq!(slice, &original[..])
+        }
        assert_eq!(ds.read_f32().unwrap(), original);

        std::fs::remove_file(&path).ok();
@@ -436,6 +436,14 @@ impl<'f> Dataset<'f> {
        &self,
        selection: &clawhdf5_format::selection::Selection,
    ) -> Result<Vec<u8>, Error> {
+        // `Selection::All` is semantically a full read — route it through
+        // the same per-file chunk cache `read_raw()` uses instead of the
+        // selection path's uncached `read_chunked_data`, so callers get
+        // consistent caching behavior regardless of which method they used
+        // to ask for "everything".
+        if matches!(selection, clawhdf5_format::selection::Selection::All) {
+            return self.read_raw();
+        }
        let dt = self.datatype()?;
        let ds = self.dataspace()?;
        let dl = self.data_layout()?;
@@ -715,7 +715,9 @@ fn multiple_chunked_datasets_share_file_cache() {
    use clawhdf5_format::datatype::{CharacterSet, Datatype, StringPadding};

    // 1-D chunked + compressed fixed-length strings (payload > compress threshold).
-    let strings: Vec<String> = (0..64).map(|i| format!("entry-{i:06}-{}", "x".repeat(80))).collect();
+    let strings: Vec<String> = (0..64)
+        .map(|i| format!("entry-{i:06}-{}", "x".repeat(80)))
+        .collect();
    let max_len = strings.iter().map(|s| s.len()).max().unwrap();
    let mut sraw = Vec::new();
    for s in &strings {
@@ -743,7 +745,9 @@ fn multiple_chunked_datasets_share_file_cache() {
    {
        let ds = b.create_dataset("mat");
        ds.with_f32_data(&mat).with_shape(&[n as u64, d as u64]);
-        ds.with_chunks(&[10, d as u64]).with_shuffle().with_deflate(6);
+        ds.with_chunks(&[10, d as u64])
+            .with_shuffle()
+            .with_deflate(6);
    }
    let bytes = b.finish().unwrap();
    let file = File::from_bytes(bytes).unwrap();
@@ -755,7 +759,10 @@ fn multiple_chunked_datasets_share_file_cache() {
    let got_mat = file.dataset("mat").unwrap().read_f32().unwrap();
    assert_eq!(got_mat, mat);
    // Read the 1-D one again to confirm the cache rebinds back correctly.
-    assert_eq!(file.dataset("strs").unwrap().read_string().unwrap(), strings);
+    assert_eq!(
+        file.dataset("strs").unwrap().read_string().unwrap(),
+        strings
+    );
 }

 #[test]
@@ -850,8 +857,14 @@ fn dense_group_links_roundtrip() {
        );
    }
    // The small (compact) group still works.
-    assert_eq!(file.dataset("small/a").unwrap().read_f64().unwrap(), vec![1.0]);
-    assert_eq!(file.dataset("small/b").unwrap().read_f64().unwrap(), vec![2.0]);
+    assert_eq!(
+        file.dataset("small/a").unwrap().read_f64().unwrap(),
+        vec![1.0]
+    );
+    assert_eq!(
+        file.dataset("small/b").unwrap().read_f64().unwrap(),
+        vec![2.0]
+    );
 }

 #[test]
@@ -908,7 +921,10 @@ fn dense_links_multiblock_fractal_heap_roundtrip() {
    b.add_group(g.finish());
    let file = File::from_bytes(b.finish().unwrap()).unwrap();

-    assert_eq!(file.group("big").unwrap().datasets().unwrap().len(), n as usize);
+    assert_eq!(
+        file.group("big").unwrap().datasets().unwrap().len(),
+        n as usize
+    );
    for i in [0, 1, 1234, n - 1] {
        assert_eq!(
            file.dataset(&format!("big/dataset_number_{i:05}"))
@@ -919,3 +935,52 @@ fn dense_links_multiblock_fractal_heap_roundtrip() {
        );
    }
 }
+
+#[test]
+fn read_selection_all_matches_read_raw_on_chunked_dataset() {
+    // read_selection(&Selection::All) is semantically a full read and must
+    // go through the same cached path as read_raw()/read_f64() — not a
+    // separate uncached code path that happens to return the same bytes.
+    use clawhdf5_format::selection::Selection;
+
+    let data: Vec<f64> = (0..500).map(|i| i as f64 * 0.5).collect();
+    let mut b = FileBuilder::new();
+    b.create_dataset("chunked")
+        .with_f64_data(&data)
+        .with_chunks(&[100])
+        .with_deflate(6);
+    let file = File::from_bytes(b.finish().unwrap()).unwrap();
+
+    let ds = file.dataset("chunked").unwrap();
+    let via_read_f64 = ds.read_f64().unwrap();
+    let via_selection_bytes = ds.read_selection(&Selection::All).unwrap();
+    let via_selection: Vec<f64> = via_selection_bytes
+        .chunks_exact(8)
+        .map(|c| f64::from_le_bytes(c.try_into().unwrap()))
+        .collect();
+
+    assert_eq!(via_read_f64, data);
+    assert_eq!(via_selection, data);
+}
+
+#[test]
+fn u64_data_roundtrip() {
+    // Values spanning the full u64 range, including ones with the high bit
+    // set that would come back negative (and wrong) if bit-cast through
+    // an i64 dataset instead of a native unsigned one.
+    let values: Vec<u64> = vec![
+        0,
+        1,
+        u64::MAX,
+        u64::MAX / 2,
+        1 << 63,
+        1_700_000_000_000_000_000,
+    ];
+    let mut b = FileBuilder::new();
+    b.create_dataset("timestamps").with_u64_data(&values);
+    let file = File::from_bytes(b.finish().unwrap()).unwrap();
+    assert_eq!(
+        file.dataset("timestamps").unwrap().read_u64().unwrap(),
+        values
+    );
+}
@@ -0,0 +1,45 @@
+# cargo-deny configuration for the clawhdf5 workspace.
+# Run: cargo deny check
+
+[graph]
+targets = []
+
+[advisories]
+# Deny all crates with known security vulnerabilities.
+version = 2
+ignore = []
+
+[licenses]
+version = 2
+# Allow MIT, Apache-2.0, BSD-2-Clause, BSD-3-Clause, ISC, Zlib — all
+# compatible with ClawHDF5's MIT license.
+allow = [
+    "MIT",
+    "Apache-2.0",
+    "Apache-2.0 WITH LLVM-exception",
+    "BSD-2-Clause",
+    "BSD-3-Clause",
+    "ISC",
+    "Zlib",
+    "Unicode-3.0",
+    "Unicode-DFS-2016",
+    "CC0-1.0",
+]
+# Emit a warning (not an error) for licenses that need manual review.
+exceptions = []
+
+[bans]
+# Warn on multiple versions of the same crate; error only on exact duplicates
+# at the same semver major to avoid false positives during dep graph churn.
+multiple-versions = "warn"
+wildcards = "allow"
+highlight = "all"
+
+# Deny known-unmaintained crates.
+deny = []
+
+[sources]
+unknown-registry = "warn"
+unknown-git = "warn"
+allow-registry = ["https://github.com/rust-lang/crates.io-index"]
+allow-git = []
@@ -1,6 +1,6 @@
 {
  "name": "@redclaw/clawhdf5",
-  "version": "2.0.0",
+  "version": "2.1.0",
  "description": "Node.js bindings for clawhdf5 — HDF5-backed agent memory with hippocampal consolidation",
  "main": "index.js",
  "types": "index.d.ts",
@@ -0,0 +1,214 @@
+# ClawHDF5 Architecture Overview
+
+*Research brief — generated 2026-08-12*
+
+---
+
+## 1. Project Identity
+
+ClawHDF5 (package prefix `clawhdf5-*`) is a **pure-Rust HDF5 implementation** combined with a **research-grade agent memory engine**. It ships zero C dependencies, targets `no_std` environments (embedded / WASM), and stores all agent state in a single portable `.h5` file.
+
+Current version: **2.1.0** (released 2026-06-03; unreleased work-in-progress is the effective HEAD).
+
+Repository: Cargo workspace with **16 crates** (plus `libaec-sys`, an internal FFI-bindings crate for the optional SZIP feature). Total size ~92K lines of Rust.
+
+---
+
+## 2. Crate Map
+
+```
+clawhdf5 workspace
+│
+├── Core HDF5
+│   ├── clawhdf5-format     — Binary parser/writer (no_std), shared type defs
+│   ├── clawhdf5-io         — I/O abstraction: buffered, mmap, async, MPI-IO stub
+│   ├── clawhdf5-filters    — Fast deflate path (zlib-ng); lz4/zstd/pcodec/szip live in format
+│   ├── clawhdf5-derive     — Proc-macro #[derive(HDF5)]
+│   ├── clawhdf5            — High-level facade (File, Dataset, FileBuilder)
+│   ├── clawhdf5-netcdf4    — NetCDF-4 compatibility shim
+│   ├── clawhdf5-accel      — CPU SIMD (AVX2, AVX-512, NEON) acceleration
+│   └── clawhdf5-gpu        — GPU compute via wgpu + hand-written WGSL shaders
+│
+├── Agent Memory
+│   ├── clawhdf5-agent      — Memory engine (20.9K lines, 32 modules)
+│   ├── clawhdf5-ann        — HNSW ANN index (default vector backend)
+│   ├── clawhdf5-migrate    — SQLite → HDF5 migration tool
+│   ├── clawhdf5-android    — Android JNI bridge
+│   └── clawhdf5-cli        — CLI (create / save / search / recall / stats / …)
+│
+├── Bindings
+│   ├── clawhdf5-py         — Python via PyO3 (pyo3/numpy 0.29)
+│   └── clawhdf5-napi       — Node.js via napi-rs (@redclaw/clawhdf5 npm package)
+│
+└── Tooling
+    └── clawhdf5-bench      — Criterion benchmark suite
+```
+
+---
+
+## 3. HDF5 Format Layer (`clawhdf5-format`)
+
+### 3.1 Parser Coverage
+
+The format crate implements a ground-up HDF5 binary parser. Notable capabilities shipped as of HEAD:
+
+| Feature | Status |
+|---------|--------|
+| Superblock v0–v4 (incl. page-buffer mode) | ✅ Full |
+| B-tree v1 (symbol, chunk) | ✅ Full |
+| B-tree v2 (link-name index type 5) | ✅ Full |
+| Fractal heap (single-direct-block) | ✅ Full |
+| Fractal heap (multi-direct-block / root indirect) | ✅ Full |
+| Fractal heap (multi-level indirect) | ❌ Not yet |
+| Dense group link storage (fractal heap + v2 B-tree) | ✅ Full |
+| Dense attribute storage | ✅ Full |
+| Compact / contiguous / chunked data layouts | ✅ Full |
+| Fixed Array chunk index | ✅ Full (incl. paged) |
+| Extensible Array chunk index | ⚠️ Partial (fixed rows only) |
+| Virtual Datasets (same-file) | ✅ Full |
+| Virtual Datasets (external-file) | ✅ Via `VdsSourceResolver` callback |
+| Filter: deflate (zlib-ng fast path) | ✅ |
+| Filter: shuffle | ✅ |
+| Filter: fletcher32 | ✅ |
+| Filter: LZ4 (id 32004) | ✅ (feature-gated) |
+| Filter: Zstandard (id 32015) | ✅ (feature-gated) |
+| Filter: Pcodec (id 32023) | ✅ (feature-gated) |
+| Filter: N-Bit (id 5) | ✅ Full (atomic, compound, array) |
+| Filter: Scale-offset D-scale / integer (id 6) | ✅ Full |
+| Filter: Scale-offset E-scale (id 6, type 1) | ✅ Full |
+| Filter: SZIP (id 4) | ✅ Feature-gated (`szip` via `libaec-sys` FFI) |
+| Datatype: fixed-point (int) | ✅ Full incl. reduced-precision + sign extension |
+| Datatype: floating-point (f32/f64/f16) | ✅ Full |
+| Datatype: string (fixed/variable) | ✅ Full |
+| Datatype: compound (class 6, v1–v5) | ✅ Full |
+| Datatype: array (class 10, v1–v5) | ✅ Full |
+| Datatype: reference | ⚠️ Partial |
+
+### 3.2 Write Path
+
+- `FileBuilder` API for high-level file construction.
+- Dense attribute/link writes via single-direct-block fractal heap + v2 B-tree (validated against h5py 3.16 / HDF5 2.0).
+- Multi-direct-block write path shipped (root indirect block).
+- Objects spanning blocks (huge-object path) not yet supported.
+- Chunked write with parallel compression (rayon, `parallel` feature).
+- Auto-shuffle (AoS→SoA byte transpose): +157–204% throughput on float data.
+
+### 3.3 Chunk Cache
+
+O(1) lookup via `slot_index: HashMap`. Cache hits return a shared `Arc` (no clone). Cache is scoped per-dataset to prevent cross-dataset index collisions.
+
+---
+
+## 4. Agent Memory Layer (`clawhdf5-agent`)
+
+### 4.1 Module Map (32 modules)
+
+| Module | Responsibility |
+|--------|----------------|
+| `knowledge` | Entity/relation graph; BFS; spreading activation; fuzzy entity resolution (Levenshtein) |
+| `consolidation` | Three-tier memory (Working → Episodic → Semantic) with importance scoring and time-decay |
+| `hybrid` | RRF (k=60) fusion of vector + BM25; exposes `merge_vector_keyword` |
+| `reranker` | Multi-factor re-ranking: temporal recency, source authority, activation weight |
+| `confidence` | Low-confidence rejection — suppresses spurious recalls |
+| `temporal` | Sorted timestamp index, session DAG, entity timeline, temporal query hints |
+| `multimodal` | Cross-modal search (text / image / audio / video) |
+| `provenance` | FNV-1a content hash, SHA-256 attributes, source attribution |
+| `anomaly` | 15 injection-pattern detectors, write rate limiter, source distribution analysis |
+| `openclaw` | `MemoryBackend` trait; Markdown ↔ HDF5 import/export |
+| `vector_search` | Flat cosine, pre-normed, SIMD, BLAS, GPU paths |
+| `ivf` / `pq` | IVF-PQ ANN for billion-scale search |
+| `bm25` | BM25 keyword index with TF-IDF |
+| `entity_extract` | Rule-based entity extraction from text chunks |
+| `wal` | CRC32-per-entry WAL; `WAL_VERSION` 2; length-prefix caps (`MAX_WAL_FIELD_LEN` = 64 MiB) |
+| `memory_strategy` | Pluggable strategies: save-every, semantic-shift, user-correction detection |
+| `decision_gate` | Sub-microsecond trivial/substantive classification |
+| `async_memory` | Tokio async wrapper (`async` feature) |
+
+### 4.2 HDF5 Schema
+
+```
+agent_memory.h5
+├── /meta               — schema_version, agent_id, embedder, embedding_dim, created_at
+├── /memory
+│   ├── chunks:         string[N]
+│   ├── embeddings:     f32[N × D]  (f16 with float16 flag — 2× space savings)
+│   ├── tombstones:     u8[N]
+│   └── norms:          f32[N]  (pre-computed L2)
+├── /sessions
+│   ├── ids:            string[S]
+│   └── summaries:      string[S]
+└── /knowledge_graph
+    ├── entity_names:   string[E]
+    ├── relation_srcs:  i64[R]
+    ├── relation_tgts:  i64[R]
+    └── relation_types: string[R]
+```
+
+### 4.3 HNSW Vector Index (`clawhdf5-ann`)
+
+- Default vector backend for `hybrid_search` (on by default via `hnsw` feature).
+- Mutable live index: `insert`, `mark_deleted` (soft-delete bitset), `compact`, serialization (format version 2).
+- Self-healing: rebuilds on drift from memory cache length.
+- Optional `parallel` feature (rayon) for `prune_connections`.
+- Outer build/insert loop is deliberately sequential (cross-iteration data dependencies).
+- Fallback: exact linear cosine scan via `--no-default-features --features float16`.
+
+### 4.4 Retrieval Pipeline
+
+```
+Agent query
+    │
+    ▼
+Hybrid search (HNSW vector + BM25)
+    │
+    ▼
+RRF fusion (k=60)
+    │
+    ▼
+Multi-factor re-ranking
+  · temporal recency
+  · source authority
+  · spreading activation weight
+    │
+    ▼
+Confidence rejection (min_score threshold + gap filter)
+    │
+    ▼
+Results
+```
+
+LongMemEval results (full `longmemeval_s` haystack, 500 questions):
+- BM25 only: 75.0% turn-level Hit@5
+- Vector only (MiniLM): 71.8%
+- Hybrid (weights 0.4/0.6 — tuned): **81.4%**
+
+---
+
+## 5. Cross-Language Bindings
+
+| Binding | Crate | Status |
+|---------|-------|--------|
+| Python | `clawhdf5-py` (PyO3 0.29 / numpy 0.29) | Build works locally; wheels not published |
+| Node.js | `clawhdf5-napi` + `packages/clawhdf5-node` | Complete package; not published to npm |
+| Android | `clawhdf5-android` (JNI) | Shipped; bounds/null checks added for JNI unsafe |
+
+---
+
+## 6. CI/CD
+
+`.gitea/workflows/ci.yml` runs `scripts/ci-test.sh` on every push/PR to `main`:
+- `rustfmt` check
+- `clippy` (zero warnings)
+- Full test suite (`cargo test --workspace`, 1,650+ tests)
+- `no_std` check (`scripts/check-nostd.sh`)
+
+---
+
+## 7. Key Design Decisions
+
+1. **Zero C dependencies** — enables `no_std`, static linking, cross-compilation, and eliminates the HDF5 C library as an attack surface. Tradeoff: manual implementation of every HDF5 format detail.
+2. **Single-file storage** — all agent state (vectors, BM25 index, knowledge graph, WAL) lives in one `.h5` file. Portability > convenience for multi-component setups.
+3. **CRC32 per WAL entry** — crash safety without journaling overhead; corrupted entry stops replay cleanly.
+4. **`float16` storage** — 2× space savings on embeddings; defaults on.
+5. **HNSW on by default** — sub-millisecond ANN at 10K–100K vectors; exact scan always available as fallback.
+6. **`parallel` feature off by default** — correctness-safe default; enables Rayon where safe (chunk compression, HNSW `prune_connections`).
--- a/Show More
+++ b/Show More