agent-security-review

# agent-security-review A holistic, adversarial review of an **agent's configuration and behaviour** — the trust anchor, not the application code. Where [`threat-modeling`](../threat-modeling/SKILL.md) models a code change and [`security-audit`](../security-audit/SKILL.md) hunts code vulnerabilities, this skill asks: *given this assembled agent config (rules, skills, MCP servers, hooks, permissions, memory), how would an attacker turn it against its owner, and what defensive gap lets them?* Pairs the static signal from [`/security-audit-config`](../../agent-src/commands/) with an adversarial three-lens pass. Output is **decision support** — surface the trade-off, name the gap; the human decides. ## When to use - A consumer asks "is my agent setup safe / could this be weaponised". - Before trusting a third-party skill pack, MCP server, or rules file. - Periodic posture review of a fleet's agent config. - Any `D`/`F` category from `/security-audit-config` that warrants depth. ## Procedure ### 1. Inventory + inspect the attack surface Inspect the config the agent actually loads and check each surface in turn: instruction files (CLAUDE.md / AGENTS.md / .cursor/rules / copilot-instructions), installed skills + their `allowed-tools`, MCP servers + their tool descriptions, hooks + lifecycle scripts, permission/auto-approve settings, persistent memory, **and CI workflows that run an AI agent** (`.github/workflows/*` invoking an agent action or CLI: check trigger — `pull_reques...