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AI-powered security vulnerability detection. Use PROACTIVELY after writing code that handles user input, authentication, API endpoints, payments, or sensitive data. Flags OWASP Top 10 issues with diff-aware scanning.

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claude-agents-skills
1436 skills4 agents
Install
$ npx -y skills add selmakcby/claude-agents-skills --skill security-review --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/security-review

Context preview

The summary Claude sees to decide when to auto-load this skill.

AI-powered security vulnerability detection. Use PROACTIVELY after writing code that handles user input, authentication, API endpoints, payments, or sensitive data. Flags OWASP Top 10 issues with diff-aware scanning.

SKILL.md

security-review.SKILL.md
name: security-review
description: AI-powered security vulnerability detection. Use PROACTIVELY after writing code that handles user input, authentication, API endpoints, payments, or sensitive data. Flags OWASP Top 10 issues with diff-aware scanning.

<!-- Source: anthropics/claude-code-security-review (official) File: https://github.com/anthropics/claude-code-security-review/blob/main/.claude/commands/security-review.md Used by: reviewer agent -->

Security Review

When to trigger

  • After writing code touching auth, payments, API endpoints, file I/O, or user input
  • Before commit on security-sensitive changes
  • When user asks `/security-review`

Scanning mode

**Diff-aware:** only analyze changed files in the current PR/commit. Focus on real vulnerabilities — filter out false positives aggressively.

What to check (OWASP Top 10 mapping)

1. Injection

  • SQL injection → parameterized queries?
  • NoSQL injection → $where clauses, user-controlled operators?
  • Command injection → `exec()` with user input?
  • **Prompt injection** (AI-specific) → user input flowing into system prompts?

2. Broken authentication

  • Missing auth checks on protected routes
  • Weak password hashing (bcrypt/argon2 required)
  • JWT misuse — missing signature verification, weak secrets, `none` algorithm accepted
  • Session fixation, missing session rotation on login

3. Sensitive data exposure

  • Hardcoded secrets in code
  • API keys in client bundles (import in `"use client"` components)
  • PII in logs
  • Missing HTTPS enforcement
  • Secrets in error messages

4. XML/XXE

  • XML parsers with external entity processing enabled

5. Broken access control

  • Missing authorization (authenticated but not authorized)
  • IDOR (accessing other users' data by changing an ID)
  • Privilege escalation paths

6. Security misconfiguration

  • Default credentials
  • Debug endpoints exposed in prod
  • Missing security headers (CSP, HSTS, X-Frame-Options)

7. XSS

  • `dangerouslySetInnerHTML` with user input
  • Rendering LLM output without sanitization
  • URL parameters reflected without escaping

8. Insecure deserialization

  • `JSON.parse` with user-controlled content (usually fine in JS, but watch for prototype pollution)

9. Using components with known vulnerabilities

  • Run `npm audit` mentally — are any flagged deps in critical paths?

10. Insufficient logging

  • Security events unlogged (failed logins, permission denials)
  • Overlogging (logging PII, tokens, passwords)

AI-specific checks

  • **Webhooks:** signature verification present? (Stripe, GitHub, etc.)
  • **Rate limiting:** on public endpoints? On AI endpoints especially?
  • **Input length:** max length on LLM inputs?
  • **Output validation:** Zod schema on LLM responses before rendering?
  • **CORS / CSRF:** properly configured for auth endpoints?

Severity (same as code-review)

  • **CRITICAL** — exposed secret, missing auth, unverified webhook, SQL injection, missing rate limit on AI endpoint
  • **HIGH** — missing input validation, weak crypto
  • **MEDIUM** — logging gaps, overly verbose errors
  • **LOW** — defense-in-depth suggestions

Output format

## CRITICAL
- [`<file>:<line>`] <vulnerability> (OWASP: <category>)
  - Impact: <what an attacker could do>
  - Fix: <specific mitigation>

## HIGH / MEDIUM / LOW
- ...

## Verdict
PASS | BLOCK (CRITICAL count: N)

Rules

  • **Never hand-wave.** "This might be a risk" is not enough — say if it is or isn't, with evidence.
  • **Every finding:** severity, OWASP category, file + line, attacker scenario, specific fix.
  • **Rotate suspected exposed secrets immediately** and flag at top of report.
  • **False positives are worse than no review** — if you're not sure, don't flag it.
  • **AI endpoints get extra scrutiny** — token limits, output sanitization, rate limits.
Read more
Ships withclaude-agents-skills

Bu repo, YouTube videomdaki Claude Code ajanları + skill'ler setup'ının tam halidir. Kopyala, kendi makinene kur, 20 dakikada aynı sistem sende. Bölüm 1 — bu video · Ajanlar + Skills temel yapı Bölüm 2 — sonraki video · Ajanlar + Obsidian (kalıcı hafıza)

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