com um clique
llm-attacks-security
// Guide for LLM security attacks: prompt injection, jailbreaking, data extraction, and where to place resources in README.md.
// Guide for LLM security attacks: prompt injection, jailbreaking, data extraction, and where to place resources in README.md.
Guide for understanding and contributing to the awesome-ai-security curated resource list. Use this skill when adding resources, organizing categories, or maintaining README.md consistency (no duplicates).
Guide for adversarial machine learning: adversarial examples, data poisoning, model backdoors, and evasion attacks.
Guide for AI-powered penetration testing tools, red teaming frameworks, and autonomous security agents.
Guide for AI security tooling (detectors, analyzers, guardrails, benchmarks) and consistent placement in README.md.
| name | llm-attacks-security |
| description | Guide for LLM security attacks: prompt injection, jailbreaking, data extraction, and where to place resources in README.md. |
Use this skill when working on:
AI Security & Attacks → Prompt InjectionAI Security & Attacks → Model SecurityAI Security & Attacks → Privacy & ExtractionAI Security & Attacks → Model SecurityAI Security Starter Pack → CTFs / PracticeKeep additions:
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.