Full course coming soon

AI System Security: Risks, Controls, and Operational Defense

7 chapters · 30 lessons

1. 1. AI Attack Surface and Threat Landscape

   4 lessons

   Map the unique security risks introduced by machine learning systems and understand how they differ from traditional application threats.

2. 2. Input Validation and Adversarial Defense

   4 lessons

   Learn to detect and mitigate adversarial inputs that manipulate model behavior or extract sensitive information.

3. 3. Output Control and Behavior Monitoring

   5 lessons

   Implement guardrails and monitoring systems to validate model outputs and detect unexpected behavior in production.

4. 4. Securing Retrieval and Knowledge Systems

   4 lessons

   Design security controls for RAG architectures, vector databases, and knowledge retrieval systems that handle sensitive data.

5. 5. Training Pipeline and Model Integrity

   4 lessons

   Protect the training process from data poisoning, backdoors, and unauthorized model modification.

6. 6. Third-Party AI Service Security Assessment

   4 lessons

   Evaluate security posture of external AI APIs, hosted models, and vendor services used in your applications.

7. 7. AI Security Operations and Incident Response

   5 lessons

   Build operational procedures to detect, respond to, and recover from AI-specific security incidents.