This guide presents six essential steps to secure AI—from visibility and risk assessment to embedded protection and operationalized security across the full AI stack and lifecycle. Sections of the comprehensive guide include:
- Understanding the AI Security Stack
- Defining a New MLSecOps Pipeline
- What Are the Risks to AI?
- Step 1: Discover Your AI Footprint
- Step 2: Test AI Models and Assess Risks
- Step 3: Secure AI Development and Deployment
- Step 4: Prevent Data Leaks and Threats During Runtime
- Step 5: Protect the Full AI and Application Stack
- Step 6: Operationalize AI Security
- Conclusion: Building Resilience in the AI Era
Each section details:
- Key Questions You Should Ask
- Challenges
- AI Security Best Practices
- How AppSOC Meets these Challenges
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