AI Security Testing Tools
Comprehensive guide to security testing tools and scanners for AI-generated code. Learn which SAST, DAST, SCA, and specialized tools work best for detecting vulnerabilities in Copilot and Cursor code.
No Single Tool Catches Everything
AI-generated code requires a defense-in-depth approach. Use multiple tools covering SAST, DAST, SCA, and secret scanning to maximize vulnerability detection. Manual review remains essential.
Security Testing Setup Checklist
Follow these 12 steps to establish comprehensive security testing. Critical items should be implemented before deploying AI-generated code.
Identify AI-generated code sections
Use version control history and comments to identify which code sections were AI-generated vs human-written.
Configure SAST tools
Set up static analysis security testing tools like SonarQube, Semgrep, or CodeQL to scan for common vulnerabilities.
Run dependency scanners
Use npm audit, pip-audit, or Snyk to identify vulnerable dependencies suggested by AI tools.
Implement secret scanning
Configure GitGuardian, TruffleHog, or GitHub Secret Scanning to catch hardcoded credentials.
Set up DAST testing
Deploy dynamic analysis tools like OWASP ZAP or Burp Suite to test running applications for vulnerabilities.
Enable API security testing
Use tools like Postman, REST Assured, or specialized API security scanners for endpoint testing.
Configure IDE security plugins
Install security linters and real-time scanners in your IDE to catch issues during development.
Implement pre-commit hooks
Add security checks to pre-commit hooks to prevent vulnerable code from being committed.
Set up CI/CD security gates
Integrate security scans into CI/CD pipeline with quality gates that fail builds on critical findings.
Configure compliance scanning
Add compliance-specific scanners for GDPR, HIPAA, PCI-DSS, or industry regulations.
Enable container security
Scan Docker images and containers with tools like Trivy, Clair, or Anchore.
Schedule regular security audits
Perform periodic manual security audits and penetration testing on AI-generated codebases.
Static Analysis (SAST)
SonarQube
ExcellentComprehensive code quality and security analysis with AI-code detection rules
Semgrep
ExcellentFast, customizable pattern matching for security vulnerabilities
CodeQL
GoodGitHub's semantic code analysis engine with extensive vulnerability database
Bandit (Python)
GoodPython-specific security linter for common security issues
Dynamic Analysis (DAST)
OWASP ZAP
ExcellentOpen-source web app scanner for runtime vulnerability detection
Burp Suite
ExcellentProfessional web security testing with manual and automated scanning
Acunetix
GoodAutomated web vulnerability scanner with low false positives
Nmap
GoodNetwork scanning and service detection for infrastructure testing
Dependency Scanning (SCA)
Snyk
ExcellentDeveloper-first security with vulnerability detection in dependencies
Dependabot
ExcellentAutomated dependency updates with security vulnerability alerts
npm audit
GoodBuilt-in Node.js dependency vulnerability scanner
OWASP Dependency-Check
GoodOpen-source SCA tool supporting multiple languages
Secret Scanning
GitGuardian
ExcellentReal-time secret detection in code, commits, and infrastructure
TruffleHog
ExcellentFind secrets accidentally committed to git repositories
GitHub Secret Scanning
GoodAutomatic detection of exposed secrets in GitHub repos
detect-secrets
GoodYelp's enterprise-friendly secret detection tool
Related Resources
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