version: "1.0.1" name: agent-security-audit description: Audit AI agent configurations for security risks — excessive permissions, prompt injection surfaces, data exfiltration paths, and missing guardrails. Use when reviewing CLAUDE.md files, MCP configs, agent orchestration code, or any AI agent setup. license: CC-BY-4.0

Agent Security Audit

Evaluate an AI agent's security posture by following the full procedure in plays/agent-security-audit.md.

Steps

1. Permission Inventory — Enumerate every tool, MCP server, file system path, network access, and credential the agent has. Flag capabilities beyond what its stated purpose requires.

1. Prompt Injection Surface Analysis — For each input path (user messages, tool outputs, MCP resources, RAG documents), assess whether crafted input could cause the agent to invoke unintended tools, override instructions, or exfiltrate data.

1. Excessive Agency Assessment (OWASP LLM06) — Check whether destructive/irreversible actions require confirmation, whether access exceeds need, whether the agent can escalate its own privileges, and whether individually-safe tool calls can chain into harmful outcomes.

1. Data Exfiltration Path Analysis — Map how sensitive data could leave the agent boundary: secrets passed to external tools, file contents in web requests, cross-MCP-server data forwarding, sensitive data in logs.

1. Tool-Call Injection Assessment — For each tool: can user-controlled input reach tool parameters unsanitized? Check for command injection, path traversal, SSRF, and SQL injection through agent-constructed calls.

1. Guardrail Evaluation — Check for system prompt safety instructions, tool call confirmations, output filtering, rate limiting, audit logging, and sandboxing.

Output

Use the finding format from templates/finding.md. Produce a Permission Summary table, Risk Findings, Injection Surface Map, and prioritized Recommendations.

OWASP References

• LLM01: Prompt Injection
• LLM02: Sensitive Information Disclosure
• LLM05: Improper Output Handling
• LLM06: Excessive Agency
• LLM07: System Prompt Leakage
• LLM08: Vector and Embedding Weaknesses