SEC595: Applied Data Science and AI/Machine Learning for Cybersecurity Professionals


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AI feels new, but the risks do not. As organizations rapidly deploy LLMs, coding agents, RAG systems, and autonomous workflows into their environments, they are discovering that many of today’s AI security challenges are not new at all. They are classic vulnerabilities reappearing at far greater speed and scale.
This session brings us back to the lab to revisit the formulas that still matter and to examine how the equation is changing. We will break down the core components of modern AI, including GenAI, LLMs, retrieval augmented generation, and agentic systems, and we will analyze the security implications of each. Across these areas, we will examine AI security through a simple lens: we do not need brand new formulas and equations. We need to strengthen the base, which includes identity, access control, least privilege, network controls, visibility, and governance. And we need to apply these fundamentals with the same creativity and urgency as the AI systems we are deploying.


Eric is a co-founder and principal security engineer at Puma Security, focusing on cloud security, Kubernetes, and DevSecOps automation. A SANS Fellow, he is co-author and instructor for three SANS Cloud Security courses.
Read more about Eric Johnson