Prompt Injection & LLM Security

About this course

As LLMs power more chatbots, agents, and business-critical applications, they've introduced a genuinely new category of security risk — one that traditional security training doesn't fully prepare you for. This course closes that gap.

Across 6 comprehensive practice tests and 600 carefully explained questions, you'll build a genuinely thorough, practitioner-level understanding of LLM security — from foundational concepts through real attack techniques, risk assessment, defense design, and organizational practice.

You'll start by understanding why LLMs introduce new security considerations in the first place — the blurred line between instructions and data that underlies nearly every risk covered in this course. From there, you'll dive deep into prompt injection techniques: direct and indirect injection, jailbreaking, obfuscation, and system prompt extraction, the actual methods attackers use in practice.

The course then covers data and privacy risks like training data memorization and PII exposure, followed by the elevated risks introduced when LLMs become agents that can take real-world action — tool-response poisoning, excessive permissions, and the classic "confused deputy" problem, now applied to AI systems.

Finally, you'll learn how to actually defend against these risks: layered input and output filtering, sandboxing, and the organizational practices — red-teaming, governance, and testing — that sustain security over time. The course closes with a look at emerging threats in this fast-moving field.

Every question comes with a detailed explanation, so you're learning as you go. Whether you're a security professional extending into AI, an AI/ML engineer building more securely, or a student preparing for a security-focused role, this course gives you the practical, evidence-based foundation to genuinely understand and defend LLM-based systems.

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