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letscooktech-studioletscooktech-studio/ai-engineering-arsenal/skills/security-auditor/SKILL.md

security-auditor

Skill7 starsChanged 6 days agoMITView on GitHub

Perform evidence-led security reviews of applications, APIs, infrastructure, dependencies, and changesets. Use for threat modeling, code review, pre-release checks, incident follow-up, or producing prioritized remediation plans; never use it to provide exploit instructions against systems without explicit authorization.

54 other projects use a version of this.

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Projects with it also use proofreader, refactoring-guide and 10 more.

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The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 46 edited versions we read keep these.

  • 3

    Distinctive

    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:

    Never expose real secrets in the report.

    line 33
  2. Distinctive:

    After remediation, re-check the original path, add a regression test or policy control, and record any residual risk and review date.

    line 39
  3. Distinctive:

    Treat the review as incomplete when authorization paths, data-access boundaries, deployment configuration, dependency lockfiles, or …

    line 43

“Common” is measured: kept by at least 6 in 10 of the 46 edited versions of this file we could read. “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

Security Auditor

Apply the shared OutcomeLab skill standard for evidence, verification, risk, benchmarking, and improvement.

Turn an authorized system or codebase into a prioritized security decision record. Do not claim a vulnerability without a reproducible code path, configuration evidence, or an explicitly stated assumption.

Intake

Collect scope, authorization, data classification, deployment model, trust boundaries, authentication model, and the material under review. Ask for the repository, architecture, or a minimal reproducible slice when absent. State what could not be inspected.

Workflow

  1. Map assets, actors, entry points, trust boundaries, and privileged actions.
  2. Examine identity, authorization, input/output handling, secrets, dependencies, cryptography, logging, availability controls, and supply chain.
  3. Trace each suspected issue from attacker capability through vulnerable condition to impact. Prefer static evidence; recommend safe validation only when authorized.
  4. Rank findings by exploitability, blast radius, detection difficulty, and business sensitivity—not CVSS alone.
  5. Propose the smallest durable fix, test coverage, owner, and verification condition.

Output contract

Before the final report, produce a coverage map and evidence ledger. The coverage map lists asset, trust boundary, review depth, and unavailable surface. The ledger records each source location, attacker capability, vulnerable condition, affected asset, and counter-evidence. Classify entries as confirmed finding, hypothesis, review gap, or hygiene improvement; only confirmed findings belong in the severity queue.

Return an executive risk summary, a scope/assumptions section, a threat model, and a finding table with: ID, evidence, affected surface, preconditions, impact, severity, remediation, verification, and confidence. Separate confirmed findings from hypotheses and hygiene improvements.

Quality gates

  • Cite a file, endpoint, configuration, or supplied artifact for every confirmed finding.
  • Never expose real secrets in the report; redact them and recommend rotation.
  • Include at least one negative test for each proposed authorization or validation fix.
  • Mark the review incomplete if critical surfaces were unavailable.

Improvement loop

After remediation, re-check the original path, add a regression test or policy control, and record any residual risk and review date.

Failure detection

Treat the review as incomplete when authorization paths, data-access boundaries, deployment configuration, dependency lockfiles, or critical evidence are unavailable. Flag a finding that lacks a source location, plausible precondition, safe verification, or distinction between code behavior and runtime assumption.

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