Community-driven AI security audit tool using interpretability techniques
Project description
Community AI Security Audit Tool
A community-driven tool for auditing AI models for security vulnerabilities using interpretability techniques. Built for cybersecurity researchers, ML engineers, and AI safety enthusiasts.
Features
- Vulnerability Scanning — Detect backdoors, adversarial vulnerabilities, data poisoning, model stealing risks, and membership inference.
- Interpretability Analysis — Apply integrated gradients, LIME, activation clustering, and more to explain model behavior.
- Risk Scoring & Reporting — Generate actionable reports (Markdown, JSON, HTML, SARIF) with severity scores and mitigation suggestions.
- Plug & Play — Swap any model provider, SIEM, or scanner without touching the core.
- Community Sharing — Share audit results, signatures, and detection rules via a lightweight database or git-based sharing.
Installation
git clone https://github.com/your-org/community-ai-audit.git
cd community-ai-audit
pip install -e .
Quick Start
# Discover all components
community-ai-audit discover
# Scan a local PyTorch model
community-ai-audit scan my_model.pt --provider local --scanners adversarial --probe-file examples/data/toy_probe.json
# Full audit with interpretability
community-ai-audit audit my_model.pt --provider local --profile standard --scanners adversarial backdoor --interpreters integrated-gradients --probe-file examples/data/toy_probe.json --input '[0.1,...'
# Generate report in HTML
community-ai-audit audit my_model.pt --provider local --output html --save report.html
Supported Providers
| Adapter | Type | Works Offline | Setup |
|---|---|---|---|
local |
PyTorch, TF, ONNX | ✅ Yes | Install torch/tensorflow |
huggingface |
transformers, diffusers | ✅ Yes | Install transformers |
openai |
GPT-4o, o1, etc. | ❌ No | Set OPENAI_API_KEY |
anthropic |
Claude-3, etc. | ❌ No | Set ANTHROPIC_API_KEY |
aws_bedrock |
All Bedrock models | ❌ No | Set AWS creds |
ollama |
Local LLMs | ✅ Yes | Install ollama |
Supported SIEMs
| Connector | Platform | Auth |
|---|---|---|
splunk |
Splunk HEC | Token |
elastic |
Elastic Security | API Key |
datadog |
Datadog Logs | API Key |
sentinel |
Microsoft Sentinel | Shared Key |
Architecture
┌─────────────┐ ┌──────────────┐ ┌─────────────┐
│ Model │────→│ Scanner(s) │────→│ Findings │
│ Adapter │ └──────────────┘ └─────────────┘
│ │
│ │────→│ Interpreter │────→│Attributions │
│ │ └──────────────┘ └─────────────┘
└─────────────┘ │ │
↓ ↓
┌────────────┐
│ Reporter │
│ (md/json/ │
│ html/sf) │
└────────────┘
[CLI] → [AuditEngine] → [Plugins] → [SIEM Connector]
See docs/ARCHITECTURE.md for the full architecture.
Documentation
| Guide | Purpose |
|---|---|
| ADAPTER_GUIDE.md | Add a new model provider (30 min) |
| SCANNER_GUIDE.md | Add a new vulnerability scanner (30 min) |
| CONNECTOR_GUIDE.md | Add a new SIEM connector (30 min) |
| INTERPRETER_GUIDE.md | Add a new interpreter (30 min) |
| PLUGIN_GUIDE.md | Quick reference for all plugins |
| ARCHITECTURE.md | System design and data flow |
| CONTRIBUTING.md | Setup, workflow, PR checklist |
| PHASE1_BENCHMARK.md | Benchmark reproducibility |
| PHASE2_CONNECTORS.md | SIEM integration guide |
Project Status
🚧 Pre-release (v0.1.0) — Core infrastructure in progress.
Contributing
See CONTRIBUTING.md for setup instructions and guidelines.
License
MIT License — see LICENSE.
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