claude-code-security-review — security grade SAFE, quality 73/100

Security audit verdict: SAFE · quality 73/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by anthropics · Claude Skill · ★ 6.3k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is claude-code-security-review safe to install? View the security audit →

Featured in: Security Auditing · Agent Security

About claude-code-security-review

Claude Code Security Reviewer An AI-powered security review GitHub Action using Claude to analyze code changes for security vulnerabilities. This action provides intelligent, context-aware security analysis for pull requests using Anthropic's Claude Code tool for deep semantic security analysis. See our blog post here for more details. Features AI-Powered Analysis: Uses Claude's advanced reasoning to detect security vulnerabilities with deep semantic understanding Diff-Aware Scanning: For PRs, only analyzes changed files PR Comments: Automatically comments on PRs with security findings Contextual Understanding: Goes beyond pattern matching to understand code semantics Language Agnostic: Works with any programming language False Positive Filtering: Advanced filtering to reduce noise and focus on real vulnerabilities Quick Start Add this to your repository's : yaml name: Security Review permissions: pull-requests: write # Needed for leaving PR comments contents: read on: pullrequest: jobs: security: runs-on: ubuntu-latest steps: uses: actions/checkout@v4 with: ref: ${{ github.event.pullrequest.head.sha github.sha }} fetch-depth: 2 uses: anthropics/claude-code-security-review@main...

Quick Facts

Stars6,292
Forks701
LanguagePython
CategoryClaude Skill
LicenseMIT
Quality Score72.5520087414352/100
Open Issues100
Last Updated2026-02-11
Created2025-08-04
Platformsclaude-code, python
Est. Tokens~6k

Compatible Skills

These tools work well together with claude-code-security-review for enhanced workflows:

  • fuzzforge_ai — semantic(0.21)+complementary+same_lang+similar_pop+shared_platform (57%)
  • mcp-scanner — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (56%)
  • Anthropic-Cybersecurity-Skills — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (56%)
  • mcp — semantic(0.26)+complementary+same_lang+similar_pop+shared_platform (54%)
  • raptor — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (51%)

claude-code-security-review alternative? Top 6 similar tools

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Frequently Asked Questions

What is claude-code-security-review?

claude-code-security-review is An AI-powered security review GitHub Action using Claude to analyze code changes for security vulnerabilities.. It is categorized as a Claude Skill with 6.3k GitHub stars.

What programming language is claude-code-security-review written in?

claude-code-security-review is primarily written in Python.

How do I install or use claude-code-security-review?

You can find installation instructions and usage details in the claude-code-security-review GitHub repository at github.com/anthropics/claude-code-security-review. The project has 6.3k stars and 701 forks, indicating an active community.

What license does claude-code-security-review use?

claude-code-security-review is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to claude-code-security-review?

The top alternatives to claude-code-security-review on Agent Skills Hub include frontend-slides, planning-with-files, claude-scientific-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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