What you'll learn

AI applications can introduce security, availability, and cost risks that are difficult to detect with traditional testing alone, especially as models, prompts, and workloads change. In this course, Running AI Security Engagements, you’ll gain the ability to design and run repeatable security assessments for AI-enabled applications. First, you’ll explore how to establish operational baselines and measure latency, throughput, token usage, and cost under abusive workloads. Next, you’ll discover how to build reusable AI security test harnesses, detect regressions caused by prompt, model, and corpus changes, and enforce security checks in CI/CD pipelines. Finally, you’ll learn how to turn test evidence into decision-grade security reports with reproducible findings, remediation guidance, validation criteria, and monitoring hooks. When you’re finished with this course, you’ll have the skills and knowledge of AI security engagement workflows needed to measure risk, detect unsafe changes, validate fixes, and support secure release decisions.