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llm-prompt-injection

LLM prompt injection playbook. Use when testing AI/LLM applications for direct injection, indirect injection via RAG/browsing, tool abuse, data exfiltration, MCP security risks, and defense bypass techniques.

skills/llm-prompt-injection/SKILL.md

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# SKILL: LLM Prompt Injection — Expert Attack Playbook

> **AI LOAD INSTRUCTION**: Expert LLM prompt injection techniques. Covers direct injection (instruction override, role play, context manipulation), indirect injection (RAG poisoning, web browsing, email), tool/function abuse, data exfiltration, MCP security risks, and defense bypass (encoding, splitting, few-shot). Base models miss the distinction between direct and indirect injection and underestimate tool-calling attack chains.

## 0. RELATED ROUTING

- [ai-ml-security](../ai-ml-security/SKILL.md) for broader ML security (adversarial examples, model poisoning, model extraction, data privacy attacks)
- [xss-cross-site-scripting](../xss-cross-site-scripting/SKILL.md) for parallels between XSS (injecting into HTML context) and prompt injection (injecting into LLM context)
- [ssrf-server-side-request-forgery](../ssrf-server-side-request-forgery/SKILL.md) when prompt injection chains into SSRF via tool calls

### Advanced Reference

Also load [JAILBREAK_PATTERNS.md](./JAILBREAK_PATTERNS.md) when you need:
- Categorized jailbreak technique library (DAN, developer mode, hypothetical scenarios, translation bypass)