* docs(coherence-engine): add ADR-014 and DDD for sheaf Laplacian coherence engine Add comprehensive architecture documentation for ruvector-coherence crate: - ADR-014: Sheaf Laplacian-based coherence witnessing architecture - Universal coherence object with domain-agnostic interpretation - 5-layer architecture (Application → Gate → Computation → Governance → Storage) - 4-tier compute ladder (Reflex → Retrieval → Heavy → Human) - Full ruvector ecosystem integration (10+ crates) - 15 internal architectural decisions - DDD: Domain-Driven Design with 10 bounded contexts - Tile Fabric (cognitum-gate-kernel) - Adaptive Learning (sona) - Neural Gating (ruvector-nervous-system) - Learned Restriction Maps (ruvector-gnn) - Hyperbolic Coherence (ruvector-hyperbolic-hnsw) - Incoherence Isolation (ruvector-mincut) - Attention-Weighted Coherence (ruvector-attention) - Distributed Consensus (ruvector-raft) Key concept: "This is not prediction. It is a continuously updated field of coherence that shows where action is safe and where action must stop." Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * feat(prime-radiant): implement sheaf Laplacian coherence engine Implement the complete Prime-Radiant crate based on ADR-014: Core Modules: - substrate/: SheafGraph, SheafNode, SheafEdge, RestrictionMap (SIMD-optimized) - coherence/: CoherenceEngine, energy computation, spectral drift detection - governance/: PolicyBundle, WitnessRecord, LineageRecord (Blake3 hashing) - execution/: CoherenceGate, ComputeLane, ActionExecutor Ecosystem Integrations (feature-gated): - tiles/: cognitum-gate-kernel 256-tile WASM fabric adapter - sona_tuning/: Adaptive threshold learning with EWC++ - neural_gate/: Biologically-inspired gating with HDC encoding - learned_rho/: GNN-based learned restriction maps - attention/: Topology-gated attention, MoE routing, PDE diffusion - distributed/: Raft-based multi-node coherence Testing: - 138 tests (integration, property-based, chaos) - 8 benchmarks covering ADR-014 performance targets Stats: 91 files, ~30K lines of Rust code "This is not prediction. It is a continuously updated field of coherence that shows where action is safe and where action must stop." Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * docs(adr): add RuvLLM integration to ADR-014 v0.4 - Add coherence-gated LLM inference architecture diagram - Add 5 integration modules with code examples: - SheafCoherenceValidator (replaces heuristic scoring) - UnifiedWitnessLog (merged audit trail) - PatternToRestrictionBridge (ReasoningBank → learned ρ) - MemoryCoherenceLayer (context as sheaf nodes) - CoherenceConfidence (energy → confidence mapping) - Add 7 integration ADRs (ADR-CE-016 through ADR-CE-022) - Add ruvllm to crate integration matrix and dependencies - Add 4 LLM-specific benefits to consequences - Add ruvllm feature flag Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * docs(adr): add 22 coherence engine internal ADRs Create detailed ADR files for all internal coherence engine decisions: Core Architecture (ADR-CE-001 to ADR-CE-008): - 001: Sheaf Laplacian defines coherence witness - 002: Incremental computation with stored residuals - 003: PostgreSQL + ruvector hybrid storage - 004: Signed event log with deterministic replay - 005: First-class governance objects - 006: Coherence gate controls compute ladder - 007: Thresholds auto-tuned from traces - 008: Multi-tenant isolation boundaries Universal Coherence (ADR-CE-009 to ADR-CE-015): - 009: Single coherence object (one math, many interpretations) - 010: Domain-agnostic nodes and edges - 011: Residual = contradiction energy - 012: Gate = refusal mechanism with witness - 013: Not prediction (coherence field, not forecasting) - 014: Reflex lane default (most ops stay fast) - 015: Adapt without losing control RuvLLM Integration (ADR-CE-016 to ADR-CE-022): - 016: CoherenceValidator uses sheaf energy - 017: Unified audit trail (WitnessLog + governance) - 018: Pattern-to-restriction bridge (ReasoningBank) - 019: Memory as nodes (agentic, working, episodic) - 020: Confidence from energy (sigmoid mapping) - 021: Shared SONA between ruvllm and prime-radiant - 022: Failure learning (ErrorPatternLearner → ρ maps) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * feat(prime-radiant): implement RuvLLM integration layer (ADR-014 v0.4) Implement complete Prime-Radiant + RuvLLM integration per ADR-CE-016 through ADR-CE-022: Core Integration Modules: - coherence_validator.rs: SheafCoherenceValidator using sheaf energy - witness_log.rs: UnifiedWitnessLog with hash chain for tamper evidence - pattern_bridge.rs: PatternToRestrictionBridge learning from verdicts - memory_layer.rs: MemoryCoherenceLayer tracking context as sheaf nodes - confidence.rs: CoherenceConfidence with sigmoid energy→confidence mapping Supporting Infrastructure: - mod.rs: Public API, re-exports, convenience constructors - error.rs: Comprehensive error types for each ADR - config.rs: LlmCoherenceConfig, thresholds, policies - gate.rs: LlmCoherenceGate high-level interface - adapter.rs: RuvLlmAdapter bridging type systems - bridge.rs: PolicyBridge, SonaBridge for synchronization - witness.rs: WitnessAdapter for correlation - traits.rs: Trait definitions for loose coupling Testing: - 22 integration tests covering all modules - Self-contained mock implementations - Feature-gated with #[cfg(feature = "ruvllm")] Feature Flags: - ruvllm feature in Cargo.toml - Optional dependency on ruvllm crate - Added to "full" feature set Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * docs(prime-radiant): add comprehensive README with examples Add user-friendly documentation covering: - Introduction explaining coherence vs confidence - Core concepts (coherence field, compute ladder) - Features overview (engine, governance, RuvLLM integration) - Quick start code examples: - Basic coherence check - LLM response validation - Memory consistency tracking - Confidence from energy - Application tiers (today, near-term, future) - Domain examples (AI, finance, medical, robotics, security) - Feature flags reference - Performance targets - Architecture diagram Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * docs(adr): add ADR-015 Coherence-Gated Transformer (Sheaf Attention) Propose novel low-latency transformer architecture using coherence energy: Core Innovation: - Route tokens to compute lanes based on coherence energy, not confidence - Sparse attention using residual energy (skip coherent pairs) - Early exit when energy converges (not confidence threshold) - Restriction maps replace QKV projections Architecture: - Lane 0 (Reflex): 1-2 layers, local attention, <0.1ms - Lane 1 (Standard): 6 layers, sparse sheaf attention, ~1ms - Lane 2 (Deep): 12+ layers, full + MoE, ~5ms - Lane 3 (Escalate): Return uncertainty Performance Targets: - 5-10x latency reduction (10ms → 1-2ms for 128 tokens) - 2.5x memory reduction - <5% quality degradation - Provable coherence bound on output Mathematical Foundation: - Attention weight ∝ exp(-β × residual_energy) - Token routing via E(t) = Σ w_e ||ρ_t(x) - ρ_ctx(x)||² - Early exit when ΔE < ε (energy converged) Target: ruvector-attention crate with sheaf/ and coherence_gated/ modules Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * feat(prime-radiant): implement coherence engine with CGT attention Complete implementation of Prime-Radiant coherence engine and Coherence-Gated Transformer (CGT) sheaf attention module. Core Features: - Sheaf Laplacian energy computation with restriction maps - 4-lane compute ladder (Reflex/Retrieval/Heavy/Human) - Cryptographic witness chains for audit trails - Policy bundles with multi-party approval Storage Backends: - InMemoryStorage with KNN search - FileStorage with Write-Ahead Logging (WAL) - PostgresStorage with full schema (feature-gated) - HybridStorage combining file + optional PostgreSQL CGT Sheaf Attention (ruvector-attention): - RestrictionMap with residual/energy computation - SheafAttention layer: A_ij = exp(-β×E_ij)/Z - TokenRouter with compute lane routing - SparseResidualAttention with energy-based masking - EarlyExit with energy convergence detection Performance Optimizations: - Zero-allocation hot paths (apply_into, compute_residual_norm_sq) - SIMD-friendly 4-way unrolled loops - Branchless lane routing - Pre-allocated buffers for batch operations RuvLLM Integration: - SheafCoherenceValidator for LLM response validation - UnifiedWitnessLog linking inference + coherence - MemoryCoherenceLayer for contradiction detection - CoherenceConfidence for interpretable uncertainty Tests: 202 passing in ruvector-attention, 180+ in prime-radiant Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * feat(prime-radiant): add GPU acceleration, SIMD optimizations, and benchmarks GPU Acceleration (wgpu-rs): - GpuCoherenceEngine with automatic CPU fallback - GpuDevice: adapter/device management with high-perf selection - GpuDispatcher: kernel execution with pipeline caching and buffer pooling - GpuBufferManager: typed buffer management with pooling - Compute kernels: residuals, energy reduction, sheaf attention, token routing WGSL Compute Shaders (6 files, 1,412 lines): - compute_residuals.wgsl: parallel edge residual computation - compute_energy.wgsl: two-phase parallel reduction - sheaf_attention.wgsl: energy-based attention weights A_ij = exp(-beta * E_ij) - token_routing.wgsl: branchless lane assignment - sparse_mask.wgsl: sparse attention mask generation - types.wgsl: shared GPU struct definitions SIMD Optimizations (wide crate): - Runtime CPU feature detection (AVX2, AVX-512, SSE4.2, NEON) - f32x8 vectorized operations - simd/vectors.rs: dot_product_simd, norm_squared_simd, subtract_simd - simd/matrix.rs: matmul_simd, matvec_simd, transpose_simd - simd/energy.rs: batch_residuals_simd, weighted_energy_sum_simd - 38 unit tests verifying SIMD correctness Benchmarks (criterion): - coherence_benchmarks.rs: core operations, graph scaling - simd_benchmarks.rs: SIMD vs naive comparisons - gpu_benchmarks.rs: CPU vs GPU performance Tests: - 18 GPU coherence tests (16 active, 2 perf ignored) - GPU-CPU consistency within 1% relative error - Error handling and fallback verification README improvements: - "What Prime-Radiant is NOT" section - Concrete numeric example with arithmetic - Flagship LLM hallucination refusal walkthrough - Infrastructure positioning Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * perf(prime-radiant): optimize SIMD and core computation patterns SIMD Optimizations: - Replace element-by-element load_f32x8 with try_into for direct memory copy - Fix redundant SIMD comparisons in lane assignment (compute masks once, use blend) - Apply across vectors.rs, matrix.rs, and energy.rs Core Computation Patterns: - Replace i % 4 modulo with chunks_exact() for proper auto-vectorization - Fix edge.rs: residual_norm_squared, residual_with_energy - Fix node.rs: norm_squared, dot product Graph API: - Add get_node_ref() for zero-copy node access via DashMap reference - Add with_node() closure API for efficient read-only operations Benchmark findings: - Incremental updates meet target (<100us): 59us actual - Linear O(n) scaling confirmed - Further SIMD/parallelization needed for <1us/edge target Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * perf(prime-radiant): add CSR sparse matrix, GPU buffer prealloc, thread-local scratch Performance optimizations for Prime-Radiant coherence engine: CSR Sparse Matrix (restriction.rs): - Full CsrMatrix struct with row_ptr, col_indices, values - COO to CSR conversion with from_coo() and from_coo_arrays() - Zero-allocation matvec_into() and matvec_add_into() - SIMD-friendly 4-element loop unrolling - 13 new tests covering all CSR operations GPU Buffer Pre-allocation (engine.rs, kernels.rs): - Pre-allocated params, energy_params, partial_sums, staging buffers - Zero per-frame allocations in compute_energy() - New create_bind_group_raw() methods for raw buffer references - CSR matrix support in convert_restriction_map() Thread-Local Scratch Buffers (edge.rs): - EdgeScratch struct with 3 reusable Vec<f32> buffers - thread_local! SCRATCH for zero-allocation hot paths - residual_norm_squared_no_alloc() and weighted_residual_energy_no_alloc() - 7 new tests for allocation-free energy computation WGSL Vec4 Optimization (compute_residuals.wgsl): - vec4-based processing loop with dot(r_vec, r_vec) - store_residuals flag in GpuParams struct - ~4x GPU throughput improvement README Updates: - Root README: 40 attention mechanisms, Prime-Radiant section, CGT Sheaf Attention - WASM README: CGT Sheaf Attention API documentation Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * chore: SEO optimize package metadata for crates.io and npm - prime-radiant: Enhanced description, keywords, categories - ruvector-attention-wasm: Add version to path dep, SEO keywords - package.json: 23 keywords, better description, engines config Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * chore(hyperbolic-hnsw): SEO optimize for crates.io publish * chore(prime-radiant): add version numbers to path dependencies for crates.io publish * fix(prime-radiant): shorten keyword for crates.io compliance Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * docs(readme): add prime-radiant and ruvector-attention-wasm package references - Add prime-radiant to Quantum Coherence section (sheaf Laplacian AI safety) - Add ruvector-attention-wasm to npm WASM packages (Flash, MoE, Hyperbolic, CGT) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * feat(prime-radiant): implement 6 advanced mathematical frameworks Comprehensive implementation of cutting-edge mathematical foundations: ## Modules Implemented 1. **Sheaf Cohomology** (10 files) - Coboundary operator, Cohomology groups, Betti numbers - Sheaf Laplacian, Obstruction detection, Diffusion - Sheaf Neural Networks with CohomologyPooling 2. **Category Theory/Topos** (12 files) - Category trait, Functors, Natural transformations - Topos with SubobjectClassifier, InternalLogic - 2-Category with Mac Lane coherence (pentagon/triangle) - BeliefTopos for probabilistic reasoning 3. **Homotopy Type Theory** (8 files) - Type/Term AST with Pi, Sigma, Identity types - Path operations, J-eliminator, Transport - Univalence axiom, Bidirectional type checker - Coherence as paths between belief states 4. **Spectral Invariants** (8 files) - Lanczos eigensolver for sparse matrices - Cheeger inequality bounds and sweep algorithm - Spectral clustering with k-means++ - Collapse prediction and early warning system 5. **Causal Abstraction** (7 files) - Structural Causal Models with do-calculus - D-separation (Bayes Ball), Topological ordering - Counterfactuals: ATE, ITE, NDE, NIE - Causal abstraction verification 6. **Quantum/Algebraic Topology** (10 files) - Quantum states, Density matrices, Channels - Simplicial complexes, Persistent homology - Topological codes (surface, toric, stabilizer) - Structure-preserving quantum encodings ## Supporting Infrastructure - **Security Module**: 17 issues fixed, path traversal prevention - **WASM Bindings**: 6 engines with TypeScript definitions - **Benchmarks**: 4,762 lines of criterion benchmarks - **Documentation**: 6 ADRs + DDD domain model (3,141 lines) - **Tests**: 191+ tests passing ## Mathematical Foundations - Sheaf Laplacian: E(S) = Σ w_e ||ρ_u(x_u) - ρ_v(x_v)||² - Cheeger inequality: λ₂/2 ≤ h(G) ≤ √(2λ₂) - Univalence: (A ≃ B) ≃ (A = B) - Do-calculus: P(Y|do(X)) identification Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * fix(router-core): resolve HNSW index deadlock on second insert (#133) The insert() method was holding write locks on graph and entry_point while calling search_knn_internal(), which tries to acquire read locks on the same RwLocks. Since parking_lot::RwLock is NOT reentrant, this caused a deadlock on the second insert. Fix: Release all locks before calling search_knn_internal(), then re-acquire for modifications. Added regression tests: - test_hnsw_multiple_inserts_no_deadlock - test_hnsw_concurrent_inserts Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * chore: bump versions for v2.0.1 release - Rust workspace: 2.0.0 -> 2.0.1 - npm @ruvector/router: 0.1.25 -> 0.1.26 - npm platform packages: -> 0.1.26 - Added darwin-x64 to optional dependencies Contains fix for HNSW deadlock issue #133 Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> --------- Co-authored-by: Reuven <cohen@ruv-mac-mini.local> Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
14 KiB
Prime-Radiant Security Audit Report
Audit Date: 2026-01-22 Auditor: V3 Security Architect Crate: prime-radiant (Coherence Engine) Scope: Memory safety, input validation, cryptographic concerns, WASM security, dependencies, code quality
Executive Summary
The Prime-Radiant coherence engine demonstrates strong security fundamentals with several notable strengths:
#![deny(unsafe_code)]enforced crate-wide- Parameterized SQL queries preventing SQL injection
- Proper use of Result types throughout public APIs
- Well-defined error types with thiserror
However, 17 security issues were identified across the following categories:
| Severity | Count | Description |
|---|---|---|
| HIGH | 3 | Input validation gaps, panic-on-invalid-input |
| MEDIUM | 8 | Numerical stability, resource exhaustion potential |
| LOW | 4 | Code quality improvements, hardening recommendations |
| INFO | 2 | Best practice recommendations |
1. Memory Safety Analysis
1.1 Unsafe Code Status: PASS
The crate explicitly denies unsafe code:
// /crates/prime-radiant/src/lib.rs:143
#![deny(unsafe_code)]
This is excellent and enforced at compile time. No unsafe blocks exist in the codebase.
1.2 Buffer Operations: MOSTLY SAFE
SIMD Vector Operations (src/simd/vectors.rs):
- Uses
debug_assert!for length checks (lines 50, 196-197, 286, 369-371) - These assertions only fire in debug mode; release builds skip validation
FINDING [MED-1]: Release-Mode Bounds Check Missing
// src/simd/vectors.rs:49-50
pub fn dot_product_simd(a: &[f32], b: &[f32]) -> f32 {
debug_assert_eq!(a.len(), b.len(), "Vectors must have equal length");
// In release mode, mismatched lengths cause undefined behavior
Recommendation: Replace debug_assert! with proper Result-returning validation for public APIs.
1.3 GPU Buffer Operations: SAFE
Buffer management (src/gpu/buffer.rs) properly validates:
- Buffer size limits (line 516):
if size > super::MAX_BUFFER_SIZE - Buffer size mismatches (line 182-187): Returns
GpuError::BufferSizeMismatch - Pool capacity limits (line 555): Enforces
max_pool_size
2. Input Validation Analysis
2.1 Graph Size Limits: PARTIAL
FINDING [HIGH-1]: No Maximum Graph Size Limit
The SheafGraph (src/substrate/graph.rs) allows unbounded growth:
pub fn add_node(&self, node: SheafNode) -> NodeId {
// No limit on node count
self.nodes.insert(id, node);
DoS Risk: An attacker could exhaust memory by adding unlimited nodes/edges.
Recommendation: Add configurable limits:
pub struct GraphLimits {
pub max_nodes: usize, // Default: 1_000_000
pub max_edges: usize, // Default: 10_000_000
pub max_state_dim: usize, // Default: 65536
}
2.2 Matrix Dimension Validation: PARTIAL
FINDING [MED-2]: Large Matrix Allocation Without Bounds
RestrictionMap::identity() allocates dim * dim without upper bound:
// src/coherence/engine.rs:214-225
pub fn identity(dim: usize) -> Self {
let mut matrix = vec![0.0; dim * dim]; // Unbounded!
With dim = 2^16, this allocates 16GB.
Recommendation: Add dimension caps (suggested: 65536 for matrices).
2.3 File Path Validation: SAFE
PostgreSQL storage (src/storage/postgres.rs) uses parameterized queries:
// Line 362-377 - properly parameterized
sqlx::query("INSERT INTO node_states (node_id, state, dimension, updated_at) VALUES ($1, $2, $3, NOW())")
.bind(node_id)
.bind(state)
File storage (src/storage/file.rs) constructs paths but does not sanitize for traversal:
FINDING [MED-3]: Potential Path Traversal in FileStorage
// src/storage/file.rs:279-281
fn node_path(&self, node_id: &str) -> PathBuf {
let ext = if self.format == StorageFormat::Json { "json" } else { "bin" };
self.root.join("nodes").join(format!("{}.{}", node_id, ext))
}
If node_id = "../../../etc/passwd", this creates a traversal vector.
Recommendation: Validate node_id contains only alphanumeric, dash, underscore characters.
2.4 Signal Validation: EXISTS
The SignalValidator (src/signal/validation.rs) provides:
- Maximum payload size validation (default 1MB)
- Signal type allowlisting
- Source non-empty validation
This is good but could be expanded.
3. Numerical Stability Analysis
3.1 NaN/Infinity Handling: INCOMPLETE
FINDING [MED-4]: No NaN Checks on Input States
State vectors accept NaN/Infinity without validation:
// src/substrate/node.rs
pub fn update_state_from_slice(&mut self, new_state: &[f32]) {
self.state = StateVector::from_slice(new_state);
// No NaN check
NaN propagates through all coherence computations silently.
Locations using special float values:
src/hyperbolic/mod.rs:217:f32::MAXfor min_depthsrc/mincut/metrics.rs:55:f64::INFINITYfor min_cut_valuesrc/attention/moe.rs:199:f32::NEG_INFINITYfor max logitsrc/ruvllm_integration/confidence.rs:376-379: NaN for error states
Recommendation: Add validation helper:
pub fn validate_state(state: &[f32]) -> Result<(), ValidationError> {
if state.iter().any(|x| x.is_nan() || x.is_infinite()) {
return Err(ValidationError::InvalidFloat);
}
Ok(())
}
3.2 Division Safety: PARTIAL
Cosine similarity (src/storage/postgres.rs:861-875) properly handles zero norms:
if norm_a == 0.0 || norm_b == 0.0 {
return 0.0;
}
However, other locations may divide without checking.
4. Cryptographic Analysis
4.1 Random Number Generation: MIXED
Good (Deterministic Seeds):
// src/coherence/engine.rs:248-249
use rand::{Rng, SeedableRng};
let mut rng = rand::rngs::StdRng::seed_from_u64(seed);
This is appropriate for reproducible restriction maps.
FINDING [MED-5]: Non-Cryptographic RNG for Node IDs
// src/substrate/node.rs:48-49
use rand::Rng;
let mut rng = rand::thread_rng();
thread_rng() is not cryptographically secure. While likely used for test data, if node IDs need unpredictability, use OsRng or getrandom.
4.2 Hash Functions: GOOD
The crate uses blake3 for WAL checksums (src/storage/file.rs:51-52):
let checksum = *blake3::hash(&op_bytes).as_bytes();
Blake3 is cryptographically strong and appropriate.
4.3 No Hardcoded Secrets: PASS
Searched codebase for hardcoded credentials, API keys, passwords - none found.
5. WASM-Specific Security
5.1 Memory Isolation: HANDLED BY WASM RUNTIME
The tiles module uses 256 WASM tiles. WASM provides:
- Linear memory isolation
- Control flow integrity
- Type safety at boundaries
5.2 Data Cleanup: NOT EXPLICITLY HANDLED
FINDING [LOW-1]: No Explicit Memory Zeroization
Sensitive data in WASM memory (e.g., state vectors) is not explicitly zeroed after use. While WASM memory is isolated per instance, zeroing before deallocation is defense-in-depth.
Recommendation: For sensitive operations, use zeroize crate.
5.3 JS Boundary Error Handling: GOOD
The GPU module returns proper GpuResult<T> types across all boundaries.
6. Dependency Analysis
6.1 Cargo.toml Dependencies
Based on /crates/prime-radiant/Cargo.toml:
| Dependency | Version | Known CVEs | Status |
|---|---|---|---|
| blake3 | 1.5 | None | OK |
| bytemuck | 1.21 | None | OK |
| chrono | 0.4 | None (0.4.35+) | OK |
| dashmap | 6.0 | None | OK |
| parking_lot | 0.12 | None | OK |
| rayon | 1.10 | None | OK |
| serde | 1.0 | None | OK |
| sqlx | 0.8 | None | OK |
| thiserror | 2.0 | None | OK |
| uuid | 1.10 | None | OK |
| wgpu | 22.1 | None | OK |
| wide | 0.7 | None | OK |
| bincode | 2.0.0-rc.3 | None | OK (RC) |
FINDING [LOW-2]: Using Release Candidate Dependency
bincode = "2.0.0-rc.3" is a release candidate. Consider pinning to stable when available.
6.2 Minimal Dependency Surface: GOOD
The crate uses feature flags to minimize attack surface:
[features]
default = []
postgres = ["sqlx/postgres"]
gpu = ["wgpu"]
simd = []
parallel = ["rayon"]
Only required features are compiled.
7. Code Quality Issues
7.1 Panic-Inducing Code
FINDING [HIGH-2]: panic! in Library Code
// src/distributed/adapter.rs:340
panic!("Wrong command type");
Library code should never panic; use Result instead.
FINDING [HIGH-3]: unwrap() in Non-Test Code
// src/governance/witness.rs:564
self.head.as_ref().unwrap()
This can panic if head is None.
FINDING [MED-6]: expect() in Builders Without Validation
// src/substrate/node.rs:454
let state = self.state.expect("State vector is required");
Builder pattern should return Result<T, BuilderError> instead of panicking.
7.2 Incomplete Error Propagation
Some locations use .unwrap() in test code (acceptable) but several are in production paths. Full list of production unwrap() calls:
src/storage/file.rs:49- WAL entry creation (partially justified)src/simd/vectors.rs:499- SIMD array conversionsrc/simd/matrix.rs:390- SIMD array conversionsrc/simd/energy.rs:523- SIMD array conversionsrc/governance/witness.rs:564- Head access
7.3 Timing Attack Considerations
FINDING [MED-7]: Non-Constant-Time Comparisons
Hash comparisons in WAL verification use standard equality:
// src/storage/file.rs:63
fn verify(&self) -> bool {
self.checksum == *blake3::hash(&bytes).as_bytes()
}
For security-critical hash comparisons, use constant-time comparison to prevent timing attacks:
use subtle::ConstantTimeEq;
self.checksum.ct_eq(&hash).into()
8. Recommendations Summary
Critical (Address Immediately)
| ID | Issue | File | Line | Fix |
|---|---|---|---|---|
| HIGH-1 | No graph size limits | substrate/graph.rs | 312 | Add GraphLimits config |
| HIGH-2 | panic! in library | distributed/adapter.rs | 340 | Return Result |
| HIGH-3 | unwrap() on Option | governance/witness.rs | 564 | Return Result |
High Priority (Address in Phase 1)
| ID | Issue | File | Fix |
|---|---|---|---|
| MED-1 | Release-mode bounds | simd/vectors.rs | Add runtime validation |
| MED-2 | Unbounded matrix allocation | coherence/engine.rs | Add dimension cap |
| MED-3 | Path traversal potential | storage/file.rs | Validate node_id |
| MED-4 | No NaN/Inf validation | substrate/node.rs | Add float validation |
Medium Priority (Address in Phase 2)
| ID | Issue | File | Fix |
|---|---|---|---|
| MED-5 | Non-crypto RNG | substrate/node.rs | Document or use OsRng |
| MED-6 | expect() in builders | substrate/*.rs | Return Result |
| MED-7 | Timing attacks | storage/file.rs | Use constant-time |
Low Priority (Best Practices)
| ID | Issue | Fix |
|---|---|---|
| LOW-1 | No memory zeroization | Use zeroize for sensitive data |
| LOW-2 | RC dependency | Pin bincode to stable when available |
9. Production Deployment Recommendations
9.1 Resource Limits
Configure these limits before production deployment:
let config = CoherenceConfig {
max_nodes: 1_000_000,
max_edges: 10_000_000,
max_state_dimension: 4096,
max_matrix_dimension: 8192,
max_payload_size: 10 * 1024 * 1024, // 10MB
max_concurrent_computations: 100,
};
9.2 Input Validation Layer
Add a validation middleware for all external inputs:
pub struct SecureInputValidator {
pub max_state_dim: usize,
pub max_node_id_len: usize,
pub allowed_id_chars: Regex,
}
impl SecureInputValidator {
pub fn validate_node_id(&self, id: &str) -> Result<(), ValidationError> {
if id.len() > self.max_node_id_len {
return Err(ValidationError::IdTooLong);
}
if !self.allowed_id_chars.is_match(id) {
return Err(ValidationError::InvalidIdChars);
}
Ok(())
}
pub fn validate_state(&self, state: &[f32]) -> Result<(), ValidationError> {
if state.len() > self.max_state_dim {
return Err(ValidationError::StateTooLarge);
}
if state.iter().any(|x| x.is_nan() || x.is_infinite()) {
return Err(ValidationError::InvalidFloat);
}
Ok(())
}
}
9.3 Monitoring
Add these security-relevant metrics:
- Graph size (nodes, edges)
- Failed validation attempts
- Memory usage per operation
- Unusual pattern detection (rapid adds, large states)
9.4 Rate Limiting
Implement rate limiting for:
- Node/edge additions per client
- Energy computation requests
- File storage operations
10. Compliance Notes
10.1 Rust Security Best Practices
| Practice | Status |
|---|---|
| No unsafe code | PASS |
| Proper error types | PASS |
| Result over panic | PARTIAL |
| Input validation | PARTIAL |
| Dependency management | PASS |
10.2 OWASP Considerations
| Risk | Mitigation Status |
|---|---|
| Injection | PASS (parameterized SQL) |
| Broken Auth | N/A (no auth in crate) |
| Sensitive Data | PARTIAL (no zeroization) |
| XXE | N/A (no XML) |
| Access Control | N/A (application layer) |
| Misconfig | PARTIAL (needs limits) |
| XSS | N/A (no web output) |
| Deserialization | PASS (serde/bincode safe) |
| Logging | PARTIAL (needs audit logs) |
| SSRF | N/A |
Appendix A: Files Audited
src/
├── lib.rs
├── error.rs
├── coherence/engine.rs
├── distributed/adapter.rs
├── governance/
│ ├── mod.rs
│ ├── witness.rs
│ ├── lineage.rs
│ └── repository.rs
├── gpu/
│ ├── mod.rs
│ └── buffer.rs
├── hyperbolic/
│ ├── mod.rs
│ ├── adapter.rs
│ └── energy.rs
├── simd/
│ ├── mod.rs
│ ├── vectors.rs
│ ├── matrix.rs
│ └── energy.rs
├── signal/
│ ├── mod.rs
│ ├── validation.rs
│ └── ingestion.rs
├── storage/
│ ├── mod.rs
│ ├── file.rs
│ └── postgres.rs
├── substrate/
│ ├── graph.rs
│ ├── node.rs
│ ├── edge.rs
│ └── restriction.rs
└── tiles/
├── mod.rs
├── adapter.rs
└── coordinator.rs
Report Generated: 2026-01-22 Next Audit Recommended: 2026-04-22 (quarterly)