agentsclimarketplace

Agent security audit team

Skill Amey-Thakur/AI-SKILLS/skills/multi-agent-teams/agent-security-audit-team

Plug-and-play skills and prompts for every AI coding agent

Install
npx -y skills add Amey-Thakur/AI-SKILLS --skill agent-security-audit-team

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 21 days oldThe repository was created 21 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
  • 4 stars4 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Run a security audit as agents that map the attack surface, review each surface in parallel, skeptic-test every finding, and assemble one report. Use when you want a codebase audited by a coordinated agent team instead of a single review pass.

SKILL.md

3.7 KB, 800 tokens by cl100k_base, as published. Nobody here has run it

Security audit team of agents

A security audit run by one agent is one reviewer's blind spots applied to the whole system. Split it: one agent maps the attack surface, one reviewer per surface works in parallel, a skeptic demands a working trigger before anything counts, and an assembler writes the report. The skeptic is the load-bearing role, because an unverified finding is a pattern match wearing a severity score.

Team

  • Recon (threat-modeling, penetration-test-prep): enumerates surfaces and trust boundaries.
  • Reviewers (security-code-review, security-engineer-role): one per surface, in parallel.
  • Exploit skeptic (vulnerability-triage): demands reachability and a repro.
  • Assembler (technical-writer-role): merges surviving findings into one report.

Shape: recon first, parallel fan-out of per-surface reviewers, a skeptic gate, then assembly.

Method

  1. Recon maps the surface before anyone reviews. Enumerate entry points: routes, queues, file uploads, deserializers, third-party callbacks, auth model, and data classification. Output surface-map.md. One agent, up front.
  2. Assign one reviewer per surface, no overlap. Each takes a trust boundary from the map and writes findings.jsonl records: surface, weakness class (CWE), location, evidence, and a claimed severity.
  3. Require a concrete trigger, not a smell. A reviewer flags "user input reaches this query unparameterized," not "SQL looks risky." No evidence line, no finding.
  4. Run the exploit skeptic as a gate. For each finding it asks: is the path reachable with realistic input, does auth block it, is there a compensating control. Downgrade or drop unreachable ones, keeping the CWE note as hardening.
  5. Score with CVSS adjusted for reachability, and dedupe. The skeptic sets final severity; the reviewer's number is a claim. Collapse one root cause reported on two surfaces into a single finding.
  6. Assemble one report ordered by risk. audit-report.md: summary, findings critical-first with repro and fix, the surfaces reviewed with nothing found so scope is legible, and residual risk. Stop when every surface has a verdict and every critical and high has a skeptic ruling.

Run it

In Claude Code, run recon as a single subagent to produce surface-map.md, then spawn one reviewer subagent per surface in a single parallel turn over a shared directory; the skeptic runs as its own subagent over findings.jsonl before the assembler reads only surviving rows. Port it to CrewAI as a recon task feeding parallel review tasks then a synthesis task, to AutoGen as a GroupChat with the skeptic gating turns, or to LangGraph as a fan-out from a recon node with a triage node before assembly.

Signals it works

  • Every surface in surface-map.md has a verdict in the report, clean ones too.
  • The skeptic drops or downgrades findings, so severity tracks reachability, not pattern count.
  • A reader reproduces every critical from the report alone.

Boundaries

This organizes an agent code audit; it is not a live penetration test, which penetration-test-prep and human testers own, nor a full design threat model beyond the recon pass. Agents miss novel logic and business-rule flaws and anything needing real credentials. What counts as critical and the disclosure path are your policy, and a human signs off before findings leave the team.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 326,984. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.