# AI Red Teaming and Assurance (Self-Paced) Canonical URL: ## Overview This course connects the work of probing an AI system with the case for putting it into service. It separates red teaming, the intentional effort to break, deceive, or abuse a system, from assurance, the documented evidence that a system merits trust for its intended use. Participants carry a full engagement from start to finish: matching test scope to the system's risk classification, setting objectives, writing rules of engagement so an exercise never turns into an incident, managing team makeup and deconfliction, and choosing techniques suited to each attack surface while weighing manual testing against automated tools. Two features set the course apart. The first is agentic AI, where exposure extends beyond what a system says to the actions it takes. The second is assurance in its own right: participants build an auditable argument structured as claim, reasoning, and evidence, supported by TEV&V records and model and system cards, and follow how it feeds a risk-acceptance decision. Hard judgment calls are addressed head on, and scenario-driven exercises rather than a lab allow procurement and oversight staff to train side by side with testers. ## What you'll learn - Distinguish red teaming from adjacent assurance activities, and place it correctly in the AI assurance lifecycle - Run a red-team engagement lifecycle from planning through reporting - Scope testing to a system's risk classification, and set objectives that produce usable results - Write rules of engagement, and handle team composition and deconfliction - Match adversarial testing techniques to the attack surface they actually address - Weigh manual expert-driven testing against automated and tool-assisted approaches - Apply probing techniques to generative AI systems - Tell a genuine red-team finding apart from an ordinary software bug - Build Test, Evaluation, Verification and Validation records that support a risk decision - Construct an assurance case as claim, argument and evidence - Interpret model cards and system cards, and judge independent evaluation results - Structure a findings report and prioritize by impact rather than technical complexity - Manage remediation and retesting, and apply human oversight as a mitigation - Recognize when a finding becomes an incident - Extend testing and assurance to foundation models and to agentic, tool-using systems ## Prerequisites General agency cybersecurity awareness training, plus familiarity with AI governance and AI/ML threat terminology, as covered in AI Security & Governance for Government Course (Self-Paced). [AI Security Monitoring and Incident Response Course (Self-Paced)](/classes/ai-security-monitoring-and-incident-response-self-paced) is helpful but not required. ## Curriculum #### Module 1 - Foundations: What Is AI Red Teaming, and Where Does It Fit in AI Assurance? - What red teaming is and is not - Where it sits in the AI assurance lifecycle - The range of assurance activities - The guidance the course draws on - Who is involved #### Module 2 - Planning and Scoping a Red-Team Engagement - The engagement lifecycle - Scoping to risk classification - Setting red-team objectives - Rules of engagement - Team composition and deconfliction #### Module 3 - Adversarial Testing Techniques for Machine Learning and Generative AI - Matching technique to attack surface - Manual versus automated and tool-assisted red teaming - Generative AI probing techniques - A preview of testing agentic and tool-using systems - Telling red-team findings apart from ordinary bugs #### Module 4 - AI Assurance Frameworks: TEVV, Assurance Cases, and Documentation - Test, Evaluation, Verification and Validation - The assurance case as claim, argument and evidence - Model cards and system cards - Independent evaluation and measurement science - From assurance documentation to a risk-acceptance decision #### Module 5 - From Findings to Fixes: Reporting, Remediation, and Human Oversight - Structuring a findings report - Prioritizing by impact rather than technical complexity - Remediation and retesting - Human oversight as a mitigation category - When a finding becomes an incident #### Module 6 - Red Teaming and Assurance for Generative and Agentic AI; Capstone Scenario - Foundation models and misuse-risk testing - Agentic AI and the expansion of the attack surface from output to action - Why red teaming and assurance are recurring rather than one-time - A capstone scenario ## FAQ ### Who is the target audience for this course? For anyone who plans, conducts, oversees or has to act on the results of adversarial testing for AI systems: AI program staff, security officers and security managers, testers and evaluators, data scientists, AI governance staff, and the procurement people who must read a vendor's assurance claims and judge whether they stand up. ### Is this course open to beginners? General agency cybersecurity awareness training, plus familiarity with AI governance and AI/ML threat terminology, as covered in AI Security & Governance for Government Course (Self-Paced) . AI Security Monitoring and Incident Response Course (Self-Paced) is helpful but not required. ### Do you offer payment plans or student financing for this course? This course does not qualify for payment plans or student financing. See our Payment Plan FAQ to find related programs that qualify. ### How long do I have access to the course materials? This course is available for 365 days. You can choose when to start your access period. Once you activate, you will have 365 days to complete it (access the course materials, quizzes, projects and videos). You may request one extension of seven (7) days. Other extension requests will be evaluated on a case-by-case basis. Videos are not downloadable. ### What is the cancellation and refund policy for this single course? For this course, you are entitled to a 90% refund (your payment less the nonrefundable 10% registration fee) within 30 days of purchase if you have not accessed the course materials. ### What’s included with my tuition? A hands-on learning experience working on projects and exercises, which is proven to boost comprehension, retention, and engagement Expert instructors who are industry professionals and experienced educators that are driven to help you succeed Expert support with answers to your questions from real instructors throughout your learning journey Top-notch curricula that have been tried and tested over many years and are consistently improved for an optimal learning experience A certificate of completion to verify your accomplishment ### Are there any additional fees or expenses? There are no extra fees or taxes for our courses. The price you see on this page is the maximum you’ll pay us. ### Do you offer any discounts for this course? We don’t currently offer discounts as we do our best to affordably price our courses. ## Pricing **Tuition:** $1049