Phase 2: Static Analysis & Automated Gates · 55 min · Python · Semgrep · SonarQube

SAST for AI Code

Six tools, 7.6% coverage. The gap is the lesson.

Real-world application: Engineers who understand why 6 industry SAST tools combined catch only 7.6% of Z3-proven vulnerabilities in AI code demonstrate awareness that no single tool is sufficient and that multi-layer defense is mandatory.

What you will learn

Configure Semgrep with custom rules targeting AI-specific defect patterns
Run multiple SAST tools and compose their findings
Explain why 6 industry tools combined catch only 7.6% of Z3-proven vulnerabilities
Build a multi-SAST pipeline that maximizes coverage through tool diversity

Introduction

SAST for AI Code

Objective

Run the multi-SAST pipeline on AI-generated code samples, compute the detection gap against Z3-proven vulnerabilities, and write custom Semgrep rules targeting AI-specific CWE patterns.

Six tools, 7.6% coverage. The gap is the lesson.

Unlock the full lesson

You've read the first 2 sections. The rest of this lesson covers The Problem, The Concept, Build, Check Yourself, Key Terms & Next — plus a hands-on lab, quiz, and project artifact.

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