agentleFS
agentkitcoagentkitco/agentkit-dev-skills/skills/security-quick-review/SKILL.md

security-quick-review

Skill0 starsChanged 14 days agoMITView on GitHub

Quick security pass over a change covering secrets, injection, auth and access checks, unsafe deserialization, dependency and config risks, with evidence. Use before merging input or auth code.

The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Untrusted input: every place data comes from a user, a request, a file, a webhook, an environment, a database field that a user can write.

    line 21
  2. Distinctive:

    Every finding needs file, line and a concrete explanation.

    line 43
  3. Distinctive:

    Do not attempt to exploit anything against live systems.

    line 44
  4. Distinctive:

    If you find a real secret, tell the user to rotate it.

    line 46

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Quick security review

This is a fast triage by an AI assistant, not a security audit or penetration test. Say so in the report. Goal: find the likely problems in the code in scope and show evidence for each.

Scope

State what you reviewed (a diff, a directory, an endpoint) and what you did not. Review the diff plus the code it calls into; a change in one place often breaks assumptions elsewhere.

Checklist (look at each, report "nothing found" if clean)

  1. Secrets: keys, tokens, passwords, private keys, connection strings in code, config, tests, fixtures, logs, CI files. Check git diff and git log -p for the scope too. Never repeat a secret value in the report; give file and line only.
  2. Untrusted input: every place data comes from a user, a request, a file, a webhook, an environment, a database field that a user can write.
  3. Injection: SQL built by string concatenation, shell commands with interpolated input, template or HTML output without escaping, path joins with user input (path traversal), regex built from input, SSRF through user-supplied URLs.
  4. Authentication and authorization: is every new route or action checked for who may call it? Can a user reach another user's data by changing an ID? Are admin paths separate and checked server-side?
  5. Data exposure: logs or errors that include tokens or personal data, overly broad API responses, debug flags, permissive CORS.
  6. Unsafe operations: deserialization of untrusted data, eval/exec, disabled TLS verification, weak randomness for tokens, home-made crypto, unbounded file uploads or request sizes.
  7. Dependencies and config: new packages (do they exist, are they maintained, is the name suspiciously close to a popular one), pinned versions, lockfile changes, new permissions in CI or cloud config.
  8. Failure behavior: what happens on error, timeout or malformed input? Does it fail closed?

Report

Scope: <reviewed / not reviewed>
HIGH: <file:line> <issue>. Exploit sketch: <how it could be abused, one or two sentences>. Fix: <specific>
MEDIUM: ...
LOW / hardening: ...
Checked, nothing found: <categories>
Could not verify: <things needing runtime, infra or secrets access>
Limits: automated triage; not an audit; get a human review for anything handling money, health or identity data.

Rules

  • Every finding needs file, line and a concrete explanation. No generic OWASP lists.
  • Do not attempt to exploit anything against live systems. Reading code and running local tests is fine.
  • Rate by realistic impact, not by how scary the category sounds.
  • If you find a real secret, tell the user to rotate it; removing it from the code does not remove it from git history.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.