This course is about securing modern AI-powered apps and web-based AI agents before they become a real problem. You will work through the security risks that appear when a normal web application starts using LLM workflows, tool calling, memory, user data, cloud access, and backend actions.
Instead of only talking about theory, the course follows a practical AI agent application and shows how it can break in realistic ways. You will see how prompt injection, indirect prompt injection, broken access control, excessive permissions, secrets exposure, and data exfiltration can happen in real systems.
You will also learn how to fix these problems with practical defenses: RBAC, tool validation, explicit data boundaries, safer permissions, human-in-the-loop checks, and better review workflows before deployment. The goal is not to make you paranoid about AI development. The goal is to help you build faster without ignoring the security basics that matter.
