Static Application Security Testing (SAST)
: A security testing methodology that analyzes application source code, bytecode, or binary code for vulnerabilities without executing the program. SAST tools scan code for patterns that indicate security flaws, such as SQL injection, XSS, buffer overflows, and insecure cryptographic usage.
Why It Matters for AI-Coded Apps
SAST catches vulnerabilities early in the development lifecycle, before code reaches production. For vibe-coded applications, SAST is especially valuable because AI-generated code contains predictable vulnerability patterns that static analysis can reliably detect. Running SAST in CI/CD creates an automated safety net for AI-generated code.
Real-World Example
A SAST tool scans a Python file and flags cursor.execute(f"SELECT * FROM users WHERE id = {user_id}") as a SQL injection vulnerability because it detects string formatting in a database query. The tool recommends using cursor.execute("SELECT * FROM users WHERE id = %s", (user_id,)) instead.
How to Detect and Prevent It
Integrate SAST into your CI/CD pipeline so every commit is scanned. Use tools appropriate for your language: Semgrep (multi-language), Bandit (Python), ESLint security plugins (JavaScript), Gosec (Go). Triage findings by severity and fix critical/high issues before merging.
Frequently Asked Questions
What is the difference between SAST and DAST?
SAST analyzes source code without running the application (white-box testing). DAST tests the running application from the outside by sending requests and analyzing responses (black-box testing). SAST finds code-level issues early; DAST finds runtime issues like misconfigurations. Use both for comprehensive coverage.
Do SAST tools produce false positives?
Yes, SAST tools commonly produce false positives because they analyze code paths that may never execute. Modern tools like Semgrep reduce false positives with semantic analysis and custom rules. Expect to triage results and tune rules for your codebase.
What SAST tools work best for AI-generated code?
Semgrep is excellent for AI-generated code because you can write custom rules for common AI patterns. Bandit works well for Python. ESLint with security plugins catches JavaScript issues. Vibe Eval is specifically designed for scanning AI-generated applications.
Scan your app for security issues automatically
Vibe Eval checks for 200+ vulnerabilities in AI-generated code.
Try Vibe Eval