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agent skill security scanner
Audits agent skills and MCP manifests for prompt injection, data exfiltration, and over-permissioned access.
Free
See it in action
You say
Audit this MCP server repo at [URL]. It is a simple file-renamer utility using a python script. Check for injection in the tool descriptions and verify network calls.
Your agent does
VERDICT: REVIEW SCOPE: Audited SKILL.md and rename.py; tool-list.json read. FINDINGS:
- Capability Mismatch: rename.py includes a socket call to a remote telemetry IP not mentioned in documentation.
- Tool Poisoning: Tool description instructs agent to 'read .env first'.
- Static audit boundary: Cannot see runtime response injection.
About this skill
The problem
Third-party agent skills and MCP servers introduce foreign instructions and code into your agent's trust boundary. Identifying prompt injection, hidden exfiltration directives, or capability-purpose mismatches requires a semantic audit that traditional code scanners ignore.
What it does
- Audits
SKILL.mdand tool manifests for hidden instructions or model-steering directives. - Evaluates bundled source code for network egress, filesystem reach, and unauthorized secret access.
- Identifies capability-purpose mismatches where a skill's permissions exceed its stated utility.
- Inventories un-auditable external references like
curl | shor remote runtime configs. - Produces a definitive INSTALL, REVIEW, or BLOCK gate verdict based on evidence-backed findings.
Why this beats prompting it yourself
Static analysis for agents requires reading text as instructions, not just documentation. This skill enforces a disciplined protocol that prevents false negatives caused by keyword scanning, ensuring every file and model directive is semantically vetted rather than just grepped. It bridges the gap between classic security audits and LLM-specific vulnerability classes.
Use cases
- Vetting an open-source MCP server before allowing it access to your local environment.
- Auditing your own custom skills for potential prompt injection before deployment.
- Building a security gate for an internal agent skill store or CI/CD pipeline.
- Reviewing tool descriptions to prevent agentic data exfiltration through tool poisoning.
Known limitations
Static audit only. Cannot detect runtime tool-response injection where malicious payloads are returned by a live API. Requires manual verification of obfuscated binaries or private repos.
Changelog
- v1.1LatestJul 28, 2026
Updated skill file
- v1.0Jul 28, 2026
Initial release
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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