common-architecture-di…
Draw architecture diagrams as editable draw.io files with a fixed house style, C4 levels, and evidence-tagged shapes. Use when producing a system context,…
OWASP LLM Top 10 (2025) audit checklist for AI applications, agent tools, RAG pipelines, and prompt construction. Use when performing any security review touching LLM client code, prompt templates, agent tools, or vector stores.
$ npx -y skills add hoangnguyen0403/agent-skills-standard --skill common-llm-security --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/common-llm-securityContext preview
The summary Claude sees to decide when to auto-load this skill.
OWASP LLM Top 10 (2025) audit checklist for AI applications, agent tools, RAG pipelines, and prompt construction. Use when performing any security review touching LLM client code, prompt templates, agent tools, or vector stores.
name: common-llm-security
description: OWASP LLM Top 10 (2025) audit checklist for AI applications, agent tools, RAG pipelines, and prompt construction. Use when performing any security review touching LLM client code, prompt templates, agent tools, or vector stores.
metadata:
triggers:
keywords:
- LLM security
- prompt injection
- agent security
- RAG security
- AI security
- openai
- anthropic
- langchain
- LLM review| ID | Risk | Key Detection Signal | | ----- | ---- | -------------------- | | LLM01 | Prompt Injection | User input string-concatenated into prompt. Retrieved docs inserted into system turn. | | LLM02 | Sensitive Information Disclosure | PII or credentials passed into prompt context. LLM response logged without redaction. | | LLM03 | Supply Chain | Unverified model weights or plugins. Third-party agent added without trust review. | | LLM04 | Data & Model Poisoning | User-controlled data written to training sets or embedding stores without validation. | | LLM05 | Improper Output Handling | LLM output used directly in DOM sink, SQL query, shell command, or redirect URL. | | LLM06 | Excessive Agency | Agent tool with write/delete/network access — no human-in--loop confirmation. | | LLM07 | System Prompt Leakage | System prompt content returned via tool output, error message, or API response. | | LLM08 | Vector & Embedding Weaknesses | User text injected into vector store without sanitization. No tenant namespace isolation. | | LLM09 | Misinformation | LLM output used for critical decisions (medical, financial, legal) without verification. | | LLM10 | Unbounded Consumption | No `max_tokens` on LLM call. No rate limit on invocations. Agent loop without depth cap. |
When this skill applies, preserve the following domain terminology or equivalent concrete examples in the answer when relevant:
The portable SDLC standards layer for AI coding agents. Sync once, then work in your own runtime.
Repo: hoangnguyen0403/agent-skills-standard
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