Awesome AI Security - Project Overview
Purpose
This is a curated collection of AI/ML security materials and resources for pentesters, red teamers, and security researchers. The goal is to keep the list AI-focused, high-signal, well-categorized, and non-duplicated.
Project Structure
code
awesome-ai-security/
├── README.md # Main resource list (curated)
├── LICENSE # License
├── .claude/
│ └── skills/ # Claude skills (this directory)
└── ref/ # Reference notes (not curated)
├── my_collect.md # Personal collection
├── Awesome-AI-Security-1/
├── awesome-ai-security-2/
├── 模型安全/ # Model security notes
├── 渗透测试相关/ # Pentesting notes
└── 网络安全相关/ # Network security notes
README.md Format Convention
Heading Structure
- •Top-level categories use
##. - •Subcategories use
###(e.g., insideAI Security & Attacks). - •Starter Pack uses bold bullets for sub-sections (e.g.,
- **CTFs / Practice**).
Link Format
- •Use full URLs, one per bullet line.
- •Add a short description in square brackets:
- https://... [Short description] - •Keep descriptions concise.
- •Do not add the same URL in multiple places.
Example Entry
markdown
### Prompt Injection - https://github.com/example/tool [Prompt injection detector]
Categorization Rules (How to Place a New Link)
- •AI Security Starter Pack: CTFs, courses, blogs, newsletters, beginner resources.
- •AI/LLM Guide: LLM fundamentals, tutorials, awesome lists.
- •AI Security & Attacks: Prompt injection, adversarial attacks, poisoning, privacy, model security.
- •AI Pentesting & Red Teaming: AI-powered pentesting tools, red teaming, MCP security tools.
- •AI Security Tools & Frameworks: AI vulnerability detection, CVE analysis, OSINT, security libraries.
- •AI Agents & Frameworks: Agent frameworks, RAG, browser automation, MCP servers.
- •AI Development & Training: Training frameworks, local models, uncensored models, prompts.
- •AI Applications: Chat assistants, deep research, search engines, code analysis, web scraping.
- •AI Image & Video: Image generation, video generation, TTS, face recognition.
- •Benchmarks & Standards: AI safety benchmarks, threat frameworks, standards.
AI-Relevance Filter
Only include AI/ML-related resources. Do not add:
- •Traditional security tools (unless AI-powered)
- •Web3/blockchain tools (unless AI-related)
- •General pentesting tools without AI integration
- •Browser vulnerabilities, phishing tools, CVE collections (unless AI-analyzed)
Duplicate Policy
No duplicate URLs in README.md. If a link fits multiple categories, pick the primary one.
Contribution Checklist
- •Check for duplicates in
README.mdbefore adding. - •Verify the resource is AI/ML-related.
- •Verify the link points to the canonical source (avoid low-value forks).
- •Keep the description concise and useful.
- •Put it into the most appropriate category.
- •Prefer minimal changes over reformatting large sections.
Data Source
For detailed and up-to-date resources, fetch the complete list from:
code
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.