Regulatory compliance for AI-powered development teams
Project description
licit
Regulatory compliance for AI-powered development teams.
licit is a standalone CLI tool that tracks AI-generated code provenance, evaluates compliance against regulatory frameworks (EU AI Act, OWASP Agentic Top 10), generates required documentation (FRIA, Annex IV), and works as a CI/CD gate — all without requiring external services or infrastructure.
The Problem
Teams using AI coding assistants (Claude Code, Cursor, Copilot, Codex) face three gaps:
- No provenance tracking — Can't distinguish AI-generated code from human-written code at scale.
- Regulatory requirements — The EU AI Act mandates documentation (FRIA, Annex IV), risk management, and transparency that no existing tool automates.
- Agentic security risks — Autonomous AI agents introduce risks (prompt injection, privilege escalation) not covered by traditional security tools.
The Solution
licit init → Auto-detect project: languages, frameworks, CI/CD, agent configs
licit trace → Track code provenance (human vs AI) from git history
licit changelog → Monitor agent config changes (CLAUDE.md, .cursorrules, etc.)
licit fria → Generate Fundamental Rights Impact Assessment (EU AI Act Art. 27)
licit annex-iv → Generate Annex IV Technical Documentation
licit report → Unified compliance report (Markdown, JSON, HTML)
licit gaps → Find compliance gaps with actionable recommendations
licit verify → CI/CD gate: exit 0 (pass) or exit 1 (fail)
licit status → Quick compliance overview
licit connect → Configure optional connectors (architect, vigil)
Quick Start
Installation
pip install licit-ai-cli
Or from source:
git clone https://github.com/your-org/licit-cli.git
cd licit-cli
pip install -e ".[dev]"
Requires Python 3.12+
Initialize
cd your-project
licit init
This auto-detects your project and creates .licit.yaml:
Project: my-app
Languages: python, typescript
Agent configs: 2 detected
CI/CD: github-actions
Testing: pytest
Security tools: vigil, semgrep
Agent configurations found:
- CLAUDE.md (claude-code)
- .cursorrules (cursor)
Created .licit.yaml
Created .licit/ directory
Track Provenance
licit trace # Analyze full git history
licit trace --since 2026-01-01 # Since specific date
licit trace --stats # Show AI vs human stats
Evaluate Compliance
licit report # Full compliance report
licit report --framework eu-ai-act # EU AI Act only
licit report --format html -o r.html # HTML output
licit gaps # What's missing?
CI/CD Integration
# .github/workflows/compliance.yml
- name: Compliance check
run: |
pip install licit-ai-cli
licit verify
Exit codes: 0 = compliant, 1 = non-compliant, 2 = partially compliant.
Frameworks Supported
| Framework | Version | Status |
|---|---|---|
| EU AI Act | Regulation (EU) 2024/1689 | V0 |
| OWASP Agentic Top 10 | 2026 | V0 |
| NIST AI RMF | AI 100-1 | Planned (V1) |
| ISO/IEC 42001 | 2023 | Planned (V1) |
EU AI Act Coverage
licit evaluates deployer obligations across key articles:
- Art. 9 — Risk management (guardrails, quality gates, security scanning)
- Art. 12 — Record keeping (git history, audit trails, provenance)
- Art. 13 — Transparency (technical documentation, config changelog)
- Art. 14 — Human oversight (review gates, dry-run, intervention capability)
- Art. 26 — Deployer obligations (agent configuration, monitoring)
- Art. 27 — FRIA (interactive 5-step questionnaire)
- Annex IV — Technical documentation (auto-generated from project metadata)
OWASP Agentic Top 10 Coverage
Maps project security posture against all 10 agentic AI risks including prompt injection, unauthorized code execution, data exfiltration, and privilege escalation.
Agent Configs Detected
licit monitors configuration files for AI coding agents:
| File | Agent |
|---|---|
CLAUDE.md |
Claude Code |
.claude/settings.json |
Claude Code |
.cursorrules |
Cursor |
.cursor/rules |
Cursor |
AGENTS.md |
GitHub Agents |
.github/copilot-instructions.md |
GitHub Copilot |
.architect/config.yaml |
architect |
.prompts/**/*.md |
Generic |
Configuration
All configuration lives in .licit.yaml:
provenance:
enabled: true
methods: [git-infer]
confidence_threshold: 0.6
store_path: .licit/provenance.jsonl
changelog:
enabled: true
watch_files:
- CLAUDE.md
- .cursorrules
- AGENTS.md
- .architect/config.yaml
frameworks:
eu_ai_act: true
owasp_agentic: true
connectors:
architect:
enabled: false
vigil:
enabled: false
reports:
default_format: markdown
include_evidence: true
include_recommendations: true
Optional Connectors
licit is fully standalone — connectors enrich, they don't enable.
| Connector | What it reads | Value added |
|---|---|---|
| architect | .architect/reports/, config |
Guardrails, quality gates, budget limits, audit trail |
| vigil | SARIF files | Security findings with severity levels |
licit connect architect --enable
licit connect vigil --enable
Project Structure
src/licit/
├── cli.py # 10 CLI commands
├── config/ # Pydantic v2 config schema + YAML loader
├── core/ # Models, project detection, evidence collection
├── provenance/ # Git analysis, heuristics, JSONL store, attestation
├── changelog/ # Agent config monitoring, diff, classification
├── frameworks/ # EU AI Act evaluator, FRIA, Annex IV, OWASP
├── connectors/ # architect + vigil integrations
├── reports/ # Unified reports, gap analysis, formatters
└── logging/ # structlog configuration
Development
# Install with dev dependencies
pip install -e ".[dev]"
# Run tests
pytest tests/ -q
# Lint
ruff check src/licit/
# Type check
mypy src/licit/ --strict
Philosophy
- Standalone — Works without any external tools. Connectors are optional.
- Filesystem-first — Everything is files in
.licit/. No database, no server. - Developer-first — CLI that fits into existing git/CI workflows.
- Language-agnostic — Detects Python, JS/TS, Go, Rust, Java projects.
- Provenance-first — Understands code origin (AI vs human) for more accurate evaluations.
Roadmap
| Version | Key Features |
|---|---|
| V0 (current) | CLI, EU AI Act, OWASP, provenance, FRIA, Annex IV, CI/CD gate |
| V0.x | Cursor/Codex session readers, PDF reports, GitHub Action |
| V1 | NIST AI RMF, ISO 42001, plugin system, Sigstore, MCP Server |
| V2 | Web dashboard, multi-project, trend analysis, AI remediation |
License
MIT — Copyright (c) 2026 Diego Alba Ruiz
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