Training Course
Adversary Intelligence: LLM Tradecraft
Agentic systems are already in the environments you’re responsible for securing. Understanding how they actually work, where they fail, and how they can be exploited is no longer optional.
In this course, you’ll learn how modern LLMs process input and generate output, how prompting strategies affect model behavior, and why the architectural properties of these systems create security implications that don’t map cleanly onto traditional network security thinking.
From there, the course moves into agentic systems: how they orchestrate tools and memory, where those patterns create exploitable gaps, and how attackers abuse them through prompt injection, jailbreaks, and insecure AI infrastructure. Labs run throughout every module, giving you hands-on experience with leading AI tooling across LLM system security, threat modeling, reverse engineering, and defensive security workflows.
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Key takeaways
- How to build and evaluate LLMs and agentic systems, including how to assess their architecture, limitations, and security implications in real enterprise environments
- How to identify and understand attacker techniques targeting LLMs and agentic systems, including prompt injection, jailbreaks, and exploitable weaknesses in AI infrastructure and agent design
- How to apply AI to defensive security workflows, including threat modeling, security testing, and AI-assisted reverse engineering using leading AI technologies
