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ai-security-tooling

ai-security-tooling

github.com/gmh5225Security6144 installsUpdated 4d ago
Repository

About ai-security-tooling

A reference skill for organizing AI and ML security tools, benchmarks, and standards. It defines tool categories, classification rules, and criteria for maintaining a focused, non-duplicated resource list.

Key features

  1. 01Categorize LLM security tools
  2. 02List adversarial ML libraries
  3. 03Organize red-teaming resources
  4. 04Classify benchmarks and standards
  5. 05Apply curation rules

Use cases

  1. 01Organizing AI security resources
  2. 02Classifying an AI security tool
  3. 03Finding resources beyond the listed examples

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/gmh5225/awesome-ai-security --skill ai-security-tooling

After installing, type/ai-security-toolingin Claude Code to confirm it loaded.

Details

From the project README

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

VendorTools
MicrosoftCounterfit, PyRIT
MetaPurpleLlama (Llama Guard, Prompt Guard, Code Shield)
NVIDIAGarak, NeMo Guardrails
IBMAdversarial Robustness Toolbox (ART)
GoogleOSS-Fuzz-Gen
ProtectAIRebuff, 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.

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