Commit graph

6 commits

Author SHA1 Message Date
ruvnet
96d8fdc172 chore(workspace): cargo fmt — mechanical whitespace fix across 427 files
Pre-existing rustfmt drift across the workspace was blocking CI's
`Rustfmt` check on PR #373 + PR #377. Running plain `cargo fmt`
reformats 427 files; no semantic changes, no logic changes, no
behavior changes — just what rustfmt already wanted.

None of the touched files are in ruvector-rabitq, ruvector-rulake,
or the new mirror-rulake workflow — those were already fmt-clean
per the per-crate checks on commits 5a4b0d782, 5f32fd450, f5003bc7b.
Drift is in cognitum-gate-kernel, mcp-brain, nervous-system,
prime-radiant, ruqu-core, ruvector-attention, ruvector-mincut,
ruvix/* and sub-crates, plus several examples.

Verified post-fmt:
  cargo check -p ruvector-rabitq -p ruvector-rulake            → clean
  cargo clippy -p ... -p ... --all-targets -- -D warnings      → clean
  cargo test   -p ... -p ... --release                         → 82/82 pass

Intentionally does NOT touch clippy drift — many more warnings
(missing docs, precision-loss casts, too-many-args, unsafe-safety-
docs) spread across unrelated crates, each category a cross-cutting
design decision that deserves its own review.

With this commit Rustfmt CI goes green on PR #373 and PR #377.
Clippy will still fail — that's honest pre-existing state for a
separate dedicated PR.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-24 10:44:02 -04:00
rUv
0092507646 feat(decompiler): LLM weight decompiler + API prober (ADR-138)
Model weight decompilation:
- GGUF v2/v3 parser (self-contained, no ruvllm dep)
- Safetensors JSON header parser
- Architecture inference from tensor shapes (GQA, FFN, vocab)
- Tokenizer extraction, quantization detection
- Witness chain for model provenance
- 6 integration tests, behind `model` feature flag

API probing (live tested):
- Probes Claude, OpenAI, Gemini APIs without weight access
- Detects: streaming, tools, system_prompt, vision capabilities
- Measures: latency, tokens/sec, tokenizer type
- Model fingerprinting via self-identification + math tests
- Verified: Gemini 2.0 Flash (556ms, 46 tok/s, all caps detected)

CLI: npx ruvector decompile --model file.gguf
     npx ruvector decompile --api gemini-2.0-flash

78 Rust tests passing.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-03 19:08:30 +00:00
rUv
6fe406aae5 feat(decompiler): graph-derived hierarchical folder structure (Phase 7)
Folder structure emerges from the dependency graph — not hardcoded keywords.

tree.rs (362 lines):
- Agglomerative clustering on inter-module edge weights
- TF-IDF naming: most discriminative strings name each folder
- Recursive depth control (configurable max_depth, min_folder_size)

inferrer.rs: infer_folder_name() with TF-IDF scoring
types.rs: ModuleTree struct, hierarchical config options
run_on_cli.rs: --output-dir prints folder tree to disk
module-splitter.js: JS-side tree builder with same approach

Key principle: tightly-coupled code shares a folder,
MinCut boundaries become folder boundaries, names from context.

59 tests passing, zero warnings.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-03 03:26:54 +00:00
rUv
84e1886451 feat(decompiler): GPU training pipeline for neural name inference (ADR-136)
Training pipeline:
- generate-deobfuscation-data.mjs: 1,200+ training pairs from fixtures + synthetic
- train-deobfuscator.py: 6M param transformer (3 layers, 4 heads, 128 embed)
- export-to-rvf.py: PyTorch → ONNX → GGUF Q4 → RVF OVERLAY
- launch-gpu-training.sh: GCloud L4 GPU (--local, --cloud-run, --spot)
- Dockerfile.deobfuscator: pytorch/pytorch:2.2.0-cuda12.1

Decompiler integration:
- NeuralInferrer behind optional `neural` feature flag
- model_path in DecompileConfig
- Falls through to pattern-based when model unavailable
- Zero binary impact without feature flag

All tests pass, cargo check clean with and without neural feature.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-03 02:08:19 +00:00
rUv
1c8bec729e fix(decompiler): review fixes, benchmarks, real-world validation
Bugs fixed:
- assert!() in witness verification → proper Err return
- Swapped property-to-name mappings in inferrer
- Escape sequences in beautifier indent_braces
- Doc comments: SHAKE-256 → SHA3-256 (correct hash function)

Performance:
- Cached regex compilation via once_cell::Lazy (7 regexes)
- HashSet for O(1) lookups (was Vec O(n))
- Optimized hex encoding with lookup table
- Added ES module export support

Benchmarks (criterion):
- 1KB: 58μs parse, 230μs pipeline
- 10KB: 581μs parse, 1.7ms pipeline
- 100KB: 5.4ms parse, 26.2ms pipeline
- 1MB: 53.5ms parse (linear scaling)

Real-world: Claude Code cli.js (10.53 MB):
- 27,477 declarations, 601,653 edges
- 1,344 HIGH confidence names (5.2%)
- 5,843 MEDIUM confidence names (22.8%)
- 24.6s total pipeline time

OSS fixtures: lodash, express, redux with self-learning loop

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-03 00:47:13 +00:00
rUv
19578402e3 feat(decompiler): MinCut-based JS decompiler with witness chains (ADR-135)
5-phase decompilation pipeline:
1. Regex-based parser extracts declarations, strings, property accesses
2. MinCut graph partitioning detects original module boundaries
3. Name inference with confidence scoring (HIGH/MEDIUM/LOW)
4. V3 source map generation (browser DevTools compatible)
5. SHAKE-256 Merkle witness chains for cryptographic provenance

Ground-truth validation:
- 5 test fixtures (Express, MCP Server, React, Multi-Module, Tools)
- Self-learning feedback loop via learn_from_ground_truth()
- 14 tests, all passing

SOTA research document covering JSNice, DeGuard, cross-version
fingerprinting, and RuVector's unique advantage combining MinCut,
IIT Phi, SONA, and HNSW for decompilation.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-03 00:04:36 +00:00