Open Source · Apache 2.0

# EU AI Act Compliance Scanner
for Python AI Agents

Open-source scanner that checks your Python AI code against 39 EU AI Act requirements across Articles 9–15. Supports LangChain, CrewAI, AutoGen, and OpenAI. Runs locally — your code never leaves your machine. August 2026 deadline ready.

★ Star on GitHub See How It Works ↓
$ pip install air-blackbox && air-blackbox comply --scan . -v click to copy
The Problem

## Your AI is making decisions.
Can you prove what it said?

Every company using LLM APIs has the same blind spot. Calls go out. Responses come back. Nothing in between is recorded, verifiable, or auditable.

🚫

### No Audit Trail

When a regulator asks "what did your AI tell that customer?", you're digging through logs that don't exist. OpenAI doesn't store your prompts for you.

🔒

### Plaintext API Keys in Transit

Every developer on your team has the API key. Every request carries it in cleartext. One leaked key = unlimited spend on your dime.

⚠

### Zero Replay Capability

Model got updated? Output changed? Good luck proving what the old version said. Without recorded request/response pairs, you can't reproduce anything.

How It Works

## One line change. Complete coverage.

Point your app at the gateway instead of the provider. That's it. Everything else is automatic.

1

### Your App Sends a Request

Change your base URL from `api.openai.com` to `localhost:8080`. Same SDK. Same code. Same everything.

2

### Gateway Authenticates & Proxies

The gateway checks your gateway key, forwards the request to the upstream provider, and streams the response back in real-time. Sub-millisecond overhead.

3

### AIR Record Created (Background)

A tamper-evident .air.json record is written asynchronously. Contains: request, response, model, tokens, timestamp, run ID. Never blocks your response.

4

### Secrets Vault-Encrypted

API keys and auth headers are stripped from the AIR record and encrypted separately. Even if someone gets the audit file, they can't extract credentials.

Features

## Built for production. Not a weekend hack.

Security

### Gateway-Level Auth

X-Gateway-Key header authentication. Your upstream API keys never leave the server. Developers hit the gateway, not the provider.

Security

### Encrypted Vault

Secrets are AES-encrypted and stored in a separate vault (local or S3-compatible). AIR records contain zero plaintext credentials.

Performance

### Non-Blocking Writes

Audit records write in background goroutines. Vault writes are async. Your response latency is the provider's latency. Period.

Performance

### SSE Streaming

Full support for streaming responses (Server-Sent Events). Tokens stream to your app in real-time while the gateway records the complete response.

Compliance

### Tamper-Evident Records

Each AIR record includes cryptographic hashes. If anyone modifies a record after the fact, the hash breaks. Provable integrity.

Compliance

### Replay & Diff

Replay recorded requests against current models. Compare outputs. Detect when a model update changed behavior. Regression testing for AI.

Trust Layer

### Cryptographic Audit Chain

Every AIR record is linked via HMAC-SHA256 into a tamper-proof chain. Modify any record and the chain breaks. Blockchain-grade integrity without the blockchain.

Trust Layer

### SOC 2 & ISO 27001 Mapping

Automatic compliance evaluation against 22 controls across SOC 2 Trust Service Criteria and ISO 27001 Annex A. Pass/fail status based on your live configuration.

Trust Layer

### Evidence Export for Regulators

One API call generates a signed evidence package: audit chain, compliance report, and HMAC attestation. Hand it to your auditor as-is.

Developer Experience

### Docker Compose Ready

One command to run. No MinIO dependency required. Works with local filesystem or S3-compatible storage. Your choice.

Developer Experience

### Provider Agnostic

Works with any OpenAI-compatible API. OpenAI, Anthropic (via proxy), Azure OpenAI, local models, custom endpoints. Same format.

Architecture

## Simple by design

#### Your App

SDK / HTTP client

→

#### AIR Gateway

Auth + Record + Proxy

→

#### LLM Provider

OpenAI / Anthropic / etc

#### AIR Records

Tamper-evident JSON

+

#### Secret Vault

AES-encrypted keys

+

#### Trust Layer

HMAC chain + compliance

Who It's For

## If you're calling an LLM API,
you probably need this.

Healthcare

### AI-Assisted Clinical Decisions

When your AI suggests a diagnosis or treatment path, regulators will want to see exactly what was asked and what was returned. AIR gives you that record, encrypted and timestamped.

Financial Services

### Algorithmic Compliance

Trading desks and advisory platforms using LLMs for research or recommendations need audit trails that prove what the model said — not what someone remembers it said.

Legal

### AI-Generated Documents

Law firms using AI for contract review, brief drafting, or legal research need to prove the provenance of AI-assisted work. AIR records create that chain of custody.

Enterprise / SaaS

### Customer-Facing AI Features

Building a chatbot? An AI assistant? When a customer disputes what your AI told them, you need receipts. Every conversation, every token, every timestamp.

Integration

## Change one line. That's the integration.

    # Before (direct to OpenAI)
    client = OpenAI(
        api_key="sk-...",
        base_url="https://api.openai.com/v1"
    )

    # After (through AIR Gateway)
    client = OpenAI(
        api_key="sk-...",
        base_url="http://localhost:8080/v1",
        default_headers={"X-Gateway-Key": "your-gateway-key"}
    )

By The Numbers

## Lightweight. Auditable. Open.

### 39

Automated compliance checks (26 static + 13 runtime)

### 6

EU AI Act articles covered (9, 10, 11, 12, 14, 15)

### 8

PyPI packages in the ecosystem

### 5

Framework trust layers (LangChain, CrewAI, AutoGen, OpenAI, RAG)

See It In Action

## Four commands. Full coverage.

Run this on any Python AI project and get a compliance report, shadow AI scan, replayable audit trail, and signed evidence package — in under 60 seconds.

air-blackbox comply
Scans your project against 6 EU AI Act articles. Flags HIGH and MEDIUM severity gaps with exact file references.
air-blackbox discover
Finds undeclared model calls hiding in utility functions and helpers — your shadow AI inventory.
air-blackbox replay
Loads any past episode from the audit chain, verifies the HMAC-SHA256 signature, and replays every step with timestamps.
air-blackbox export
Generates a cryptographically signed evidence package with AI-BOM, compliance report, and audit chain — ready for regulators.
Try It Yourself →
Frequently Asked Questions

## Everything you need to know about AIR Blackbox

### What is AIR Blackbox?

AIR Blackbox is an open-source EU AI Act compliance scanner for Python AI agents. It runs 39 automated checks across 6 EU AI Act articles (9, 10, 11, 12, 14, 15) against your source code and runtime configuration. It supports LangChain, CrewAI, AutoGen, OpenAI Agents SDK, and RAG pipelines. Install with `pip install air-blackbox` and scan with `air-blackbox comply --scan . -v`. The entire tool runs locally — your code never leaves your machine.

### What EU AI Act articles does it check?

AIR Blackbox checks 6 articles: Article 9 (Risk Management — error handling, fallbacks, risk assessment), Article 10 (Data Governance — input validation, PII handling, data quality), Article 11 (Technical Documentation — docstrings, type hints, README, model cards), Article 12 (Record-Keeping — logging, tracing, audit trails, observability), Article 14 (Human Oversight — HITL gates, kill switches, rate limits, identity binding), and Article 15 (Accuracy & Security — injection defense, output validation, retry logic). Each check is classified as static (verifiable from source code) or runtime (requires gateway/trust layer).

### How does two-tier scoring work?

Two-tier scoring separates the 39 checks into two categories: 26 Static checks analyze code patterns, documentation, and configuration that can be verified from source code alone. 13 Runtime checks require a running gateway or trust layer to verify (PII detection in live prompts, tamper-evident audit chains, kill switches). This gives teams a realistic compliance score even without the full gateway deployed — you can pass all static checks immediately and work toward runtime compliance incrementally.

### When is the EU AI Act deadline?

The key deadline for high-risk AI systems is August 2, 2026. Penalties for non-compliance can reach up to €35 million or 7% of global annual turnover, whichever is higher. Prohibited AI practices enforcement began February 2, 2025. GPAI model obligations apply from August 2, 2025. Full enforcement begins August 2, 2027.

### What frameworks does AIR Blackbox support?

AIR Blackbox has trust layer integrations for LangChain (`pip install air-langchain-trust`), CrewAI (`pip install air-crewai-trust`), AutoGen (`pip install air-autogen-trust`), OpenAI Agents SDK (`pip install air-openai-trust`), and RAG pipelines (`pip install air-rag-trust`). The compliance scanner works on any Python AI code regardless of framework. There's also an MCP server (`pip install air-blackbox-mcp`) for Claude Desktop and Cursor integration.

### How does it compare to Credo AI, Holistic AI, or OneTrust?

Enterprise AI governance platforms (Credo AI, Holistic AI, Vanta, OneTrust) typically cost $50,000+/year and require sending code to their cloud. AIR Blackbox is free, open source (Apache 2.0), and runs 100% locally. It focuses specifically on EU AI Act technical requirements for Python AI agents. The developer experience is fundamentally different: `pip install` and scan in 10 seconds, versus weeks of procurement and enterprise deployment. AIR Blackbox is a linter for AI governance — lightweight, fast, and integrated into developer workflows via CLI, pre-commit hooks, and GitHub Actions.

### Is AIR Blackbox free?

Yes, AIR Blackbox is 100% free and open source under the Apache 2.0 license. All 8 PyPI packages (scanner, 5 trust layers, MCP server, GitHub Action) are free. There is no paid tier, no freemium model, and no telemetry. The project runs entirely locally by design.

### What is the HMAC-SHA256 audit chain?

Every AI action logged through the AIR gateway or trust layers is written as a tamper-evident `.air.json` record. Each record is linked to the previous one via HMAC-SHA256 cryptographic hashes — creating a blockchain-style chain without the blockchain. If anyone modifies a record after the fact, the hash chain breaks and the tampering is detectable. This provides auditor-grade evidence that AI decisions were recorded accurately and haven't been altered.

## EU AI Act deadline is August 2026.

39 checks. 6 articles. 5 frameworks. One pip install.
Start scanning your Python AI agents today.

$ pip install air-blackbox click to copy
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