- Fundamental concepts of AI security
After completing this module, you'll be able to:
- Understand and describe the basic concepts of AI security
- Describe the three layers of AI architecture
- Describe new, AI specific attack techniques
- Security controls that you can implement in AI systems to increase the security posture of AI environments
After completing this module, you'll be able to:
- Describe security controls for AI systems
- Understand when these controls should be used
- Understand the types of attacks these controls mitigate
- Introduction to AI security testing
After completing this module, you'll be able to:
- Describe AI red teaming
- Understand the three categories of AI red teaming
- Plan an AI red teaming exercise
Overview
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Syllabus
- Fundamentals of AI security
- Introduction
- Basic concepts of AI security
- AI architecture layers
- AI jailbreaking
- AI prompt injection
- AI model manipulation
- Data exfiltration
- AI overreliance
- Module assessment
- Summary
- AI security controls
- Introduction
- Review AI open-source libraries
- Content filters
- Implement AI data security
- Create metaprompts
- Ground AI systems
- Implement application security best practices for AI enabled applications
- Module assessment
- Summary
- Introduction to AI security testing
- What is AI red teaming?
- The three categories of AI red teaming
- Planning AI red teaming
- Module assessment
- Summary