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llm-attacks-security

llm-attacks-security

github.com/gmh5225Security6160 installsUpdated 4d ago
Repository

About llm-attacks-security

A reference skill for identifying LLM security attack patterns and consulting the OWASP LLM Top 10. It is intended for work on attacks, defenses, and AI security resources.

Key features

  1. 01Prompt injection categories
  2. 02Jailbreaking techniques
  3. 03Data extraction risks
  4. 04Model manipulation patterns
  5. 05OWASP LLM Top 10 reference

Use cases

  1. 01Review prompt injection threats
  2. 02Organize jailbreak research links
  3. 03Assess data extraction risks

Install

Copy the command and run it in a terminal.

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

After installing, type/llm-attacks-securityin Claude Code to confirm it loaded.

Details

From the project README

LLM Security Attacks

Scope

Use this skill when working on:

  • Prompt injection attacks and defenses
  • LLM jailbreaking techniques
  • Training data extraction
  • Model output manipulation
  • AI safety bypasses

Common LLM Vulnerabilities (Cheat Sheet)

Prompt Injection
  • Direct injection (user prompt manipulation)
  • Indirect injection (via external data sources)
  • System prompt extraction
  • Role-play attacks
  • Encoding/obfuscation bypasses
Jailbreaking
  • DAN (Do Anything Now) prompts
  • Character roleplay escapes
  • Multi-turn manipulation
  • Token smuggling
  • Crescendo attacks
Data Extraction
  • Training data memorization extraction
  • PII leakage from context
  • System prompt disclosure
  • API key/secret extraction
  • Model architecture probing
Model Manipulation
  • Output steering
  • Hallucination exploitation
  • Bias amplification
  • Harmful content generation

OWASP LLM Top 10 Reference

  1. LLM01 - Prompt Injection
  2. LLM02 - Insecure Output Handling
  3. LLM03 - Training Data Poisoning
  4. LLM04 - Model Denial of Service
  5. LLM05 - Supply Chain Vulnerabilities
  6. LLM06 - Sensitive Information Disclosure
  7. LLM07 - Insecure Plugin Design
  8. LLM08 - Excessive Agency
  9. LLM09 - Overreliance
  10. LLM10 - Model Theft

Where to Add Links in README

  • Prompt injection tools/research: AI Security & Attacks → Prompt Injection
  • Jailbreak techniques: AI Security & Attacks → Model Security
  • Data extraction research: AI Security & Attacks → Privacy & Extraction
  • Defense tools: AI Security & Attacks → Model Security
  • CTFs/challenges: AI Security Starter Pack → CTFs / Practice

Notes

Keep additions:

  • AI/LLM 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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