Course Details

This class is designed to introduce students to the most effective tools and techniques for applying cutting edge deep learning based artificial intelligence to cybersecurity tasks. By leveraging AI driven automation, students will explore new ways to enhance security workflows, improve threat detection, and optimize vulnerability research. We will take a deep dive into modern AI architectures, focusing on how deep learning models can assist in areas such as reverse engineering and vulnerability research. Students will learn to solve real world cybersecurity challenges, integrating AI driven solutions into their daily operations. The course will provide hands-on experience with advanced agent driven security automation techniques. Through practical exercises, students will gain proficiency in using AI to automate security tasks. By the end of the course, attendees will have the skills and knowledge to incorporate deep learning based AI solutions into their cybersecurity workflows, enhancing both efficiency and effectiveness.

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Details last updated June 29, 2026

About the Instructor:

Richard Johnson is the founder of Fuzzing IO and Metaframe AI and an internationally recognized industry leader in fuzzing, vulnerability research, reverse engineering and cybersecurity applications of deep learning. He has published dozens of research articles, presentations, and open source tools that have helped advance the field of fuzzing and reverse engineering. He is also widely known as the instructor of the premier fuzzing and agentic vulnerability research training programs available at industry cybersecurity conferences worldwide. Richard has been a professional vulnerability researcher and reverse engineer for over 20 years and has built teams from the ground up at Cisco Talos and Oracle Cloud to discover vulnerabilities at scale through fuzzing.