Course Outline
Introduction to AI Red Teaming
- Understanding the AI threat landscape.
- The roles of red teams in AI security.
- Ethical and legal considerations.
Adversarial Machine Learning
- Types of attacks: evasion, poisoning, extraction, and inference.
- Generating adversarial examples (e.g., FGSM, PGD).
- Targeted versus untargeted attacks and success metrics.
Testing Model Robustness
- Evaluating robustness under various perturbations.
- Exploring model blind spots and failure modes.
- Stress testing classification, vision, and NLP models.
Red Teaming AI Pipelines
- AI pipeline attack surfaces: data, model, and deployment layers.
- Exploiting insecure model APIs and endpoints.
- Reverse engineering model behavior and outputs.
Simulation and Tooling
- Utilizing the Adversarial Robustness Toolbox (ART).
- Red teaming with tools like TextAttack and IBM ART.
- Sandboxing, monitoring, and observability tools.
AI Red Team Strategy and Defense Collaboration
- Developing red team exercises and objectives.
- Communicating findings to blue teams.
- Integrating red teaming into AI risk management frameworks.
Summary and Next Steps
Requirements
- A solid understanding of machine learning and deep learning architectures.
- Practical experience with Python and machine learning frameworks (such as TensorFlow or PyTorch).
- Familiarity with cybersecurity principles or offensive security techniques.
Audience
- Security researchers.
- Offensive security teams.
- AI assurance specialists and red team professionals.
Testimonials (2)
I really enjoyed learning about AI attacks and the tools out there to begin practicing and actively using for security testing. I took a lot of knowledge away which I didn't have at the beginning and the course met what I hoped it would be. My favorite part shown from the training was Comet Browser and was amazed at what it could do. Definitely something will be looking into more. Overall it was a great course and enjoyed learning all OWASP GenAI Top 10.
Patrick Collins - Optum
Course - OWASP GenAI Security
The profesional knolage and the way how he presented it before us
