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. (triggers: LLM security, prompt injection, agent security, RAG security, AI security, openai, anthropic, langchain, LLM review)
90
87%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
| 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-the-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. |
user turn, never interpolated into system prompts.19a1140
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