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 .github/workflows/security.yml:

name: Security Review

permissions:
  pull-requests: write  # Needed for leaving PR comments
  contents: read

on:
  pull_request:

jobs:
  security:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
        with:
          ref: ${{ github.event.pull_request.head.sha || github.sha }}
          fetch-depth: 2
      
      - uses: anthropics/claude-code-security-review@main
        with:
          comment-pr: true
          claude-api-key: ${{ secrets.CLAUDE_API_KEY }}

Configuration Options

Action Inputs

Action Outputs

How It Works

Architecture

claudecode/
├── github_action_audit.py  # Main audit script for GitHub Actions
├── prompts.py              # Security audit prompt templates
├── findings_filter.py      # False positive filtering logic
├── claude_api_client.py    # Claude API client for false positive filtering
├── json_parser.py          # Robust JSON parsing utilities
├── requirements.txt        # Python dependencies
├── test_*.py               # Test suites
└── evals/                  # Eval tooling to test CC on arbitrary PRs

Workflow

1. PR Analysis: When a pull request is opened, Claude analyzes the diff to understand what changed
2. Contextual Review: Claude examines the code changes in context, understanding the purpose and potential security implications
3. Finding Generation: Security issues are identified with detailed explanations, severity ratings, and remediation guidance
4. False Positive Filtering: Advanced filtering removes low-impact or false positive prone findings to reduce noise
5. PR Comments: Findings are posted as review comments on the specific lines of code

Security Analysis Capabilities

Types of Vulnerabilities Detected

• Injection Attacks: SQL injection, command injection, LDAP injection, XPath injection, NoSQL injection, XXE
• Authentication & Authorization: Broken authentication, privilege escalation, insecure direct object references, bypass logic, session flaws
• Data Exposure: Hardcoded secrets, sensitive data logging, information disclosure, PII handling violations
• Cryptographic Issues: Weak algorithms, improper key management, insecure random number generation
• Input Validation: Missing validation, improper sanitization, buffer overflows
• Business Logic Flaws: Race conditions, time-of-check-time-of-use (TOCTOU) issues
• Configuration Security: Insecure defaults, missing security headers, permissive CORS
• Supply Chain: Vulnerable dependencies, typosquatting risks
• Code Execution: RCE via deserialization, pickle injection, eval injection
• Cross-Site Scripting (XSS): Reflected, stored, and DOM-based XSS

False Positive Filtering

The tool automatically excludes a variety of low-impact and false positive prone findings to focus on high-impact vulnerabilities:

• Denial of Service vulnerabilities
• Rate limiting concerns
• Memory/CPU exhaustion issues
• Generic input validation without proven impact
• Open redirect vulnerabilities

The false positive filtering can also be tuned as needed for a given project's security goals.

Benefits Over Traditional SAST

• Contextual Understanding: Understands code semantics and intent, not just patterns
• Lower False Positives: AI-powered analysis reduces noise by understanding when code is actually vulnerable
• Detailed Explanations: Provides clear explanations of why something is a vulnerability and how to fix it
• Adaptive Learning: Can be customized with organization-specific security requirements

Installation & Setup

GitHub Actions

Follow the Quick Start guide above. The action handles all dependencies automatically.

Local Development

To run the security scanner locally against a specific PR, see the evaluation framework documentation.

Claude Code Integration: /security-review Command

By default, Claude Code ships a /security-review slash command that provides the same security analysis capabilities as the GitHub Action workflow, but integrated directly into your Claude Code development environment. To use this, simply run /security-review to perform a comprehensive security review of all pending changes.

Customizing the Command

The default /security-review command is designed to work well in most cases, but it can also be customized based on your specific security needs. To do so:

1. Copy the security-review.md file from this repository to your project's .claude/commands/ folder.
2. Edit security-review.md to customize the security analysis. For example, you could add additional organization-specific directions to the false positive filtering instructions.

Custom Scanning Configuration

It is also possible to configure custom scanning and false positive filtering instructions, see the docs/ folder for more details.

Testing

Run the test suite to validate functionality:

cd claude-code-security-review
# Run all tests
pytest claudecode -v

Support

For issues or questions:

• Open an issue in this repository
• Check the GitHub Actions logs for debugging information

License

MIT License - see LICENSE file for details.