Protecting Your ML Systems from Attack
Complete each module to build your security engineering skills
Interactive guide to the OWASP Top 10 vulnerabilities with specific examples for AI/ML systems.
Gamified code review challenge. Find security flaws in AI/ML code before time runs out!
Build threat models for AI features using an interactive drag-and-drop interface.
Hands-on lab to refactor insecure code. Fix hard-coded secrets and implement proper patterns.
Visualize encryption concepts. See how data is protected in transit and at rest.
Generate a custom security checklist for your capstone project based on your stack.
By the end of this session, you'll be able to:
Map OWASP risks to AI/ML systems and APIs
Spot hard-coded secrets and insecure patterns
Protect data in transit and at rest
Systematically identify attack vectors
Use environment variables and secure patterns
Build actionable security checklist for capstone