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AI Regulation Compliance Scanner

Open-source CLI to evaluate AI systems against EU AI Act, UK AI principles, and NIST AI RMF.

v1.0 Scope

Implemented

  • Multi-regulation rule evaluation via YAML rule packs (eu-ai-act, uk-ai, nist-rmf)
  • Structured system profile input (--input JSON/YAML)
  • Compliance statuses per requirement: pass, partial, fail, not_applicable
  • Gap scoring and recommendation generation
  • Report outputs:
    • text
    • json (canonical machine-readable schema)
    • html
    • pdf
  • CI quality gates:
    • pytest -q
    • ruff check .
    • mypy scanner
    • python -m build

Out of Scope

  • Automatic legal interpretation beyond rule-based checks
  • Fairlearn/AIF360 and SHAP/LIME runtime integrations

Install

pip install ai-regulation-scanner

For local development:

pip install -e '.[dev]'

Quick Start

# Evaluate all supported regulations from a structured profile
ai-scan --input ./profile.yaml --regulation eu-ai-act,uk-ai,nist-rmf --format json --output ./report.json

# Render HTML report
ai-scan --input ./profile.yaml --regulation eu-ai-act,uk-ai --format html --output ./report.html

# Render PDF report
ai-scan --input ./profile.yaml --regulation eu-ai-act,uk-ai,nist-rmf --format pdf --output ./report.pdf

Input Model (--input)

Supported extensions: .json, .yaml, .yml.

metadata:
  system_name: "Example AI System"
  owner: "AI Governance"
description: "Clinical triage assistant"
use_case: "medical diagnosis support"
domain: "healthcare"
controls:
  risk_management_system: true
  data_governance: true
  technical_documentation: true
  human_oversight: false
evidence:
  - id: "ev-1"
    description: "Risk management plan and risk register"
    tags: ["risk management"]
  - "model card and technical documentation"

CLI Contract

  • --regulation: comma-separated values from eu-ai-act,uk-ai,nist-rmf
  • --format: text|json|html|pdf
  • --output: optional for text/json/html, required for pdf

Exit Codes

  • 0: Minimal/limited risk category
  • 1: High-risk category
  • 2: Prohibited category
  • 3: Validation/runtime error (input/args/output)

Canonical JSON Report Shape

Top-level keys:

  • metadata
  • generated_at
  • risk_assessment
  • regulations
  • summary_scores
  • findings
  • recommendations
  • evidence_gaps

Release & Publishing

  • GitHub Actions CI workflow enforces quality gates on PR/main.
  • GitHub Actions Release workflow runs on v* tags.
  • PyPI publish uses Trusted Publishing (id-token: write).
  • Setup guide: docs/pypi-trusted-publishing.md

License

Apache 2.0 - See LICENSE

Disclaimer

This tool provides compliance guidance only and does not constitute legal advice. Always consult qualified legal counsel for regulatory decisions.

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