Agent skill · security · semgrep
llm-security
Security guidelines for LLM applications based on OWASP Top 10 for LLM 2025. Use when building LLM apps, reviewing AI security, implementing RAG systems, or asking about LLM vulnerabilities like 'prompt injection' or 'check LLM security'. IMPORTANT: Always consult this skill when building chatbots, AI agents, RAG pipelines, tool-using LLMs, agentic systems, or any application that calls an LLM API (OpenAI, Anthropic, Gemini, etc.) — even if the user doesn't explicitly mention security. Also use when users import 'openai', 'anthropic', 'langchain', 'llamaindex', or similar LLM libraries.
Why this skill is useful
Provides detailed security guidelines and specific rule files for mitigating LLM vulnerabilities that the AI wouldn't generate on its own.
What it needs
About 3k tokens when loaded. Last updated 2026-07-28. 258 stars on the source repository.
What this skill does
LLM Security Guidelines (OWASP Top 10 for LLM 2025) Security rules for building secure LLM applications, based on the OWASP Top 10 for LLM Applications 2025. How to Use This Skill Proactive mode — When building or reviewing LLM applications, automatically check for relevant security risks based on the application pattern. You don't need to wait for the user to ask about LLM security. Reactive mode — When the user asks about LLM security, use the mapping below to find relevant rule files with detailed vulnerable/secure code examples. Workflow 1. Identify what the user is building (see "What Are You Building?" below) 2. Check the priority rules for that pattern 3. Read the specific rule files from rules/ for code examples 4. Apply the secure patterns or flag vulnerable ones What Are You Building? Use this to quickly identify which rules matter most for the user's task: Building... Priority Rules ------------- --------------- Chatbot / conversational AI Prompt Injection (LLM01), System Prompt Leakage (LLM07), Output Handling (LLM05), Unbounded Consumption (LLM10) RAG system Vector/Embedding Weaknesses (LLM08), Prompt Injection (LLM01), Sensitive Disclosure (LLM02), Misinformation (LLM09) AI agent with tools Excessive Agency (LLM06), Prompt Injection (LLM01), Output Handling (LLM05), Sensitive Disclosure (LLM02) Fine-tuning / training Data Poisoning (LLM04), Supply Chain (LLM03), Sensitive Disclosure (LLM02) LLM-powered API Unbounded Consumption (LLM10), Prompt Injection (LLM01), Output Handling (LLM05), Sensitive Disclosure (LLM02) Content generation Misinformation (LLM09), Output Handling (LLM05), Prompt Injection (LLM01) Categories Critical Impact LLM01: Prompt Injection (rules/prompt-injection.md) - Prevent direct and indirect prompt manipulation LLM02: Sensitive Information Disclosure (rules/sensitive-disclosure.md) - Protect PII, credentials, and proprietary data LLM03: Supply Chain (rules/supply-chain.md) - Secure model sources, training data, and dependencies LL …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills semgrep/llm-security