| name | ai-security-tooling |
| description | Guide for AI security tooling (detectors, analyzers, guardrails, benchmarks) and consistent placement in README.md. |
AI Security Tooling
Scope
Use this skill when adding or organizing:
- LLM security tools (guardrails, detectors)
- Adversarial ML libraries
- AI vulnerability scanners
- Model safety tools
- Security benchmarks and frameworks
Tool Categories
LLM Security Tools
- Guardrails: NeMo Guardrails, LLM Guard, Rebuff
- Detectors: Vigil-LLM, Nova Framework, Garak
- Scanners: ModelScan, AI Security Analyzer
Adversarial ML Libraries
- Attack libraries: ART, CleverHans, Foolbox, TextAttack
- Defense libraries: SecML
- Fuzzing: OSS-Fuzz-Gen, Brainstorm
AI Red Teaming
- Microsoft: Counterfit, PyRIT
- Meta: PurpleLlama
- NVIDIA: Garak, NeMo Guardrails
Benchmarks
- Robustness: RobustBench
- Jailbreak: JailbreakBench
- Safety: Stanford AIR-Bench
- Hallucination: Vectara Leaderboard
Standards & Frameworks
- MITRE ATLAS: AI threat matrix
- NIST AI RMF: Risk management framework
- OWASP: LLM Top 10, GenAI Security Project
Categorization Rules
- LLM guardrails/detectors →
AI Security & Attacks → Model Security
- Prompt injection tools →
AI Security & Attacks → Prompt Injection
- Adversarial ML libraries →
AI Security & Attacks → Adversarial Attacks or AI Security Libraries
- AI RE/debugging tools →
AI Security Tools & Frameworks → AI Reverse Engineering
- AI vulnerability scanners →
AI Security Tools & Frameworks → AI Vulnerability Detection
- Benchmarks →
Benchmarks & Standards
- MCP security tools →
AI Pentesting & Red Teaming → AI Security MCP Tools
Quality Bar
- Prefer canonical repos
- Avoid forks unless they add meaningful features
- Add short descriptions
- Never duplicate an existing URL
- Tool must be AI/ML-focused
Key Vendor Tools
| Vendor | Tools |
|---|
| Microsoft | Counterfit, PyRIT |
| Meta | PurpleLlama (Llama Guard, Prompt Guard, Code Shield) |
| NVIDIA | Garak, NeMo Guardrails |
| IBM | Adversarial Robustness Toolbox (ART) |
| Google | OSS-Fuzz-Gen |
| ProtectAI | Rebuff, LLM Guard, ModelScan |
Notes
Keep additions:
- AI/ML security focused
- Non-duplicated URLs
- Minimal structural changes
Data Source
For detailed and up-to-date resources, fetch the complete list from:
https://raw.githubusercontent.com/gmh5225/awesome-ai-security/refs/heads/main/README.md
Use this URL to get the latest curated links when you need specific tools, papers, or resources not covered in this skill.
