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 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 malware analysis, reverse engineering, vulnerability research, and penetration testing. Students will learn to train, fine-tune, and apply large language models (LLMs) to solve real-world cybersecurity challenges, integrating AI-driven solutions into their daily operations. The course will provide hands-on experience with model training, embeddings, vector search, and advanced 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.

Learn how to attack and defend Kubernetes, Linux and containers from Jay Beale, the creator of Bastille Linux, the Center for Internet Security’s first Linux security benchmark, and two Kubernetes tools: the Peirates attack tool and the Bust-a-Kube CTF cluster. In this fully hands-on course, you’ll get access to our cloud training environment, where you’ll have a Kali Linux system filled with capture-the-flag (CTF) virtual machines and a Kubernetes cluster, which you will attack and defend.