Secure AI Code & Libraries with Static Analysis
Completed by Jay Robinson
March 6, 2026
4 hours (approximately)
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What you will learn
Configure Bandit, Semgrep, PyLint to detect AI vulnerabilities: insecure model deserialization, hardcoded secrets, unsafe system calls in ML code.
Apply static analysis to fix AI vulnerabilities (pickle exploits, input validation, dependencies); create custom rules for AI security patterns.
Implement pip-audit, Safety, Snyk for dependency scanning; assess AI libraries for vulnerabilities, license compliance, and supply chain security.
Skills you will gain
- Category: Dependency Analysis
- Category: Vulnerability Scanning
- Category: Program Implementation
- Category: Application Security
- Category: Secure Coding
- Category: AI Personalization
- Category: AI Security
- Category: Continuous Integration
- Category: CI/CD
- Category: DevSecOps
- Category: Open Source Technology
- Category: MLOps (Machine Learning Operations)
