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🛡️ Anchor Core (anchor-audit)

The Deterministic Runtime Governance & Compliance Kernel for Autonomous AI Systems.

PyPI Version License

Current release: 6.0.3 · Python 3.10–3.13

Anchor is a high-performance, dual-language (Rust/Python) infrastructure library designed to enforce strict regulatory invariants, architectural boundaries, and safety safeguards around autonomous AI agents and LLM application pipelines in real-time.

By executing compiled Abstract Syntax Tree (AST) query matchers and single-pass Deterministic Finite Automaton (DFA) regex sets, Anchor operates with zero-copy memory boundaries—designed to keep per-call overhead low. See benchmarks/bench_guard.py to measure it on your hardware.


🏎️ Core Architectural Horsepower

  • Fast static scanning: Rust backend engine utilizing parallel directory walking via rayon and memory-mapped files (memmap2).
  • Zero-Copy Memory Boundaries: Leverages PyO3 zero-copy buffer bridges to consume incoming network data frames straight from host ASGI server pools (like FastAPI) with zero heap allocation overhead.
  • Asymmetric Cryptographic Identity: Every compiled audit log is bundled into an tamper-evident Decision Audit Chain (DAC) block, sealed locally using Ed25519 asymmetric keys and verified via constant-time hashing (subtle::ConstantTimeEq).
  • Active Self-Healing Interception: Moves beyond passive post-mortem dashboards. If an active consumer agent drifts into an invariant violation, Anchor's runtime layer intercepts the thread, halts execution, and injects dynamic, domain-agnostic rerouting directives on the fly.

🏛️ Comprehensive Regulatory Scope

Anchor maps rules to the provisions they relate to (a pattern match is not a legal finding). Coverage includes:

  1. EU Artificial Intelligence Act (Regulation EU 2024/1689): Complete mapping from Chapter II Article 5 Prohibited Practices (subliminal manipulation, facial scraping safeguards) to Chapter III Articles 6–27 High-Risk System obligations (6-month log retention tracking under Art 12/19, Article 14 human override levers), stretching up to Article 99 turnover penalty metrics.
  2. U.S. Securities and Exchange Commission (SEC / FINRA): Hard automated boundaries protecting algorithmic trading setups under SEC Regulation SCI (System capacity loop circuit breakers), Exchange Act Rule 15c3-5 (Pre-trade credit and risk limit validation), and Cybersecurity Form 8-K outbound data exfiltration gates.
  3. Industry Frameworks: Built-in support for FINOS OSERA AI supply-chain resiliency blueprints, OWASP Top 10 LLM security controls, NIST AI RMF, and ISO/IEC 42001 standards.

📦 High-Velocity Installation

Deploy the compiled binary kernel straight into your production cluster workspace:

pip install anchor-audit

Anchor pulls in its runtime dependencies automatically (Click, HTTPX, PyYAML, cryptography, wrapt, GitPython and the tree-sitter grammars), so the anchor command is usable straight after install.

Optional extras:

pip install "anchor-audit[providers]"   # OpenAI, Anthropic, Groq, Cohere, Ollama, ...
pip install "anchor-audit[server]"      # FastAPI/ASGI gateway (anchor.app) + uvicorn
pip install "anchor-audit[dev]"         # pytest, black, mypy

The CLI, the @guard decorator and the static scanner need none of these extras.

6.0.3 release highlights

  • Telemetry remains explicitly opt-in and performs no network dispatch by default.
  • Governance signatures are line-ending independent across Windows, macOS, and Linux.
  • The package metadata, wheel smoke test, secret scanning, and developer extras are aligned with the pyproject.toml build.
  • The committed governance public key is rotated; the private signing key is generated and retained outside the repository.

Initialize your local asymmetric cryptographic repository identity:

anchor init

Run a parallel static code safety audit across your local workspace:

anchor check .

🔌 Runtime Integration

Wrap a high-privilege agent routine or LLM invocation with a decorator. @guard only protects functions you wrap; unwrapped code is not covered.

from anchor import guard

@guard(domain="finance")
def execute_algorithmic_trade(order_payload):
    # If the autonomous agent tries to route an un-vetted market order,
    # Anchor audits the call payload before the function body runs and returns a BLOCKED_BY_ANCHOR directive on a match.
    return route_order_to_exchange(order_payload)

from anchor.guard import guard is the equivalent spelling if you prefer to import the decorator directly. Both are exercised by tests/test_readme_example.py.


🌐 The AnimusLab Institution Network

Anchor Core acts as the local spoke auditing engine that feeds seamlessly into the wider, unified decentralized coordination hub ecosystem:

Maintained by AnimusLab.


⚠️ Limitations

  • @guard (Layer 2) covers only the functions you decorate. Keyword/pattern checks can be rephrased around; treat Anchor as one deterministic layer in defense-in-depth.
  • Telemetry is off by default. Set ANCHOR_TELEMETRY=on to opt in; see docs/telemetry.md for exactly what is sent.
  • Static rules are pattern/AST based. Known detection gaps are tracked as xfail tests in tests/unit/test_detection_gaps.py.

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anchor_audit-6.0.3-cp310-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl CPython 3.10 abi3 Linux glibc 2.17+ ARM64 Details
anchor_audit-6.0.3-cp310-abi3-macosx_11_0_arm64.whl CPython 3.10 abi3 macOS 11.0+ ARM64 Details
anchor_audit-6.0.3-cp310-abi3-macosx_10_12_x86_64.whl CPython 3.10 abi3 macOS 10.12+ x86-64 Details

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