LLM & API Security: AI Penetration Testing Bootcamp

About this course

This course contains the use of artificial intelligence.

We only charge a fee solely for the time invested in building this comprehensive curriculum.

Most people who work with LLM applications are tool installers. They can pull a Docker image, call an API, paste a jailbreak prompt they found on Twitter, and screenshot the result. That's a demo. It is not a defensible security assessment, and it will not survive five minutes of questioning from a CISO, a hiring manager, or a compliance auditor who asks: what exactly did you test, what did you not test, and how do you know your fix actually holds under regression?

That gap — between "I tried a jailbreak" and "I can architect, test, harden, and govern a production LLM system" — is the entire reason this course exists. In 2026, LLM applications aren't chatbots anymore. They're customer service systems, financial workflows, health tooling, developer copilots, and agentic API orchestration layers with real data, real tool access, and real blast radius. The attack surface isn't just the prompt box. It's the API gateway, the identity layer, the retrieval pipeline, the tool registry, the deployment pipeline, and the audit trail behind all of it. Testing only the chat window is like inspecting a building by knocking on the front door and ignoring the wiring, plumbing, and fire exits.

This course fixes that with 100 sequential, hands-on labs — not slides, not theory dumps. Every lab follows the same zero-failure operating contract: pre-flight check, snapshot, build, verify, and rollback. You cannot break anything you can't immediately undo, which means you move fast without fear. Each lab explains the outcome you're aiming for, the mechanism behind it in plain language, exactly what success looks like on your screen, and three specific troubleshooting fixes when something goes sideways — because real engineers hit real friction, and pretending otherwise doesn't pre

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