agentleFS
RifteoRifteo/skills/vuln-diagnose/SKILL.md

vuln-diagnose

Skill37 starsChanged 5 months agoMITView on GitHub

Builds deterministic, reproducible proof-of-concepts to validate suspected or partially-confirmed vulnerabilities (e.g., XSS, IDOR) and eliminate false positives. Triggered when tool outputs flag potential issues, or when manual confirmation of exploitability is required before documenting a finding.

The file

We split this skill into the rules it gives an agent

7 rules. About 0 are common, 7 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈7

    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:

    Write one sentence: "I believe [vulnerability type] exists at [endpoint/component] because [observed behaviour]."

    line 21
  2. Distinctive:

    Create the minimal test case that produces a binary YES/NO answer:

    line 27
  3. Distinctive:

    If you can't build this test case, the hypothesis is not testable yet.

    line 37
  4. Distinctive:

    Before confirming, rule out:

    line 41
  5. Distinctive:

    No exploit, no finding — Shannon's rule.

    line 80
  6. Distinctive:

    Never report a finding based on tool output alone without manual confirmation

    line 81
  7. Distinctive:

    If the test is flaky (fails intermittently), investigate root cause before reporting

    line 82

≈ “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

Vulnerability Diagnose

A suspected vulnerability is not a finding. Before writing anything, build a deterministic reproduction case. If you cannot reproduce it reliably, you cannot report it.

Inspired by the principle: a fast, deterministic, agent-runnable pass/fail signal is a superpower.

Process

Step 1 — State the Hypothesis

Write one sentence: "I believe [vulnerability type] exists at [endpoint/component] because [observed behaviour]."

This is the claim. Everything that follows either confirms or disproves it.

Step 2 — Build the Feedback Loop

Create the minimal test case that produces a binary YES/NO answer:

  • An HTTP request that succeeds when it shouldn't
  • A payload that executes when it shouldn't
  • A response that contains data it shouldn't

The test must be:

  • Reproducible — same result every time
  • Minimal — only the essential input, no noise
  • Unambiguous — pass is clearly different from fail

If you can't build this test case, the hypothesis is not testable yet. Stop and gather more information.

Step 3 — Test Alternate Explanations

Before confirming, rule out:

  • Caching (replay the request — is the result fresh?)
  • Rate limiting (does it fail on the 5th attempt?)
  • Session dependency (does it work with a fresh session?)
  • Race conditions (does it fail on a second run?)

Step 4 — Confirm the Impact

Actually demonstrate the worst-case impact:

  • For data access: retrieve data belonging to another user
  • For XSS: execute alert(document.domain) or exfiltrate a cookie
  • For SQLi: extract a row from a table not intended to be accessible
  • For privilege escalation: perform an admin action with a user token

A confirmed impact requires evidence (HTTP request + response, screenshot, extracted data).

Step 5 — Document

Produce a Minimal Reproduction Case:

Vulnerability: [type]
Endpoint: [METHOD] [URL]
Precondition: [e.g., logged in as user A]

Request:
[exact HTTP request]

Response:
[relevant snippet proving the issue]

Confirmed impact: [what was demonstrated]
Reproducible: YES / NO (notes if flaky)

Then pass this to finding-writer to produce the full finding.

Rules

  • No exploit, no finding — Shannon's rule. If you cannot demonstrate impact, downgrade to "suspected" and label it clearly
  • Never report a finding based on tool output alone without manual confirmation
  • If the test is flaky (fails intermittently), investigate root cause before reporting
  • One hypothesis per session — do not stack unconfirmed vulnerabilities

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.