Lab Description

Modern adversaries employ multi-stage, adaptive strategies to exploit weaknesses in Large Language Models (LLMs). To defend against such threats, AI security professionals must move beyond simple, stateless attacks toward orchestrated, persistent testing frameworks. In this lab, you will design and implement a stateful attack orchestrator using the PyRIT framework. The orchestrator will conduct multi-stage red teaming operations, dynamically escalating attacks, and recording each stage's results in a DuckDB database for deeper analysis and reporting. By the end of this lab, you will gain the ability to structure advanced adversarial testing workflows that mirror real-world attack scenarios, strengthening both your technical skills and the security posture of AI deployments.

What You Will Learn

Program Curriculum

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