AI for Vulnerability Assessment and Code Security

After this lesson, you will be able to: Use AI-powered SAST tools (Snyk, Checkmarx) to find/prioritize vulnerabilities in code.

SAST = Static Application Security Testing, scan source code for vulns. Modern tools layer ML to reduce false positives, generate fixes, and prioritize by exploitability.

Prerequisites:AI for Security Operations (SOC)

Old SAST vs AI-augmented

Old SAST flagged 1000 issues, half false positives, no priority guidance. Modern (Snyk, Checkmarx, GitHub Advanced Security): same scan + ML triage + auto-fix PRs + reachability analysis (is the vuln actually called?).

Where AI helps in AppSec

1
1. SAST triage, drop false positives.
2
2. Reachability, only alert on exploitable code paths.
3
3. Auto-remediation suggestions.
4
4. Code review. PR-time vuln detection.
5
5. Secret scanning + classification (real vs test).

Vendor lineup

Snyk (most popular for npm/maven/pypi). Checkmarx (enterprise SAST). GitHub Advanced Security (built into GitHub). Veracode (legacy enterprise). Semgrep (open source rules).

←AI for Security Operations (SOC)

Back to AI Application: Cybersecurity

AI for Penetration Testing and Red Teaming→