SEC411: AI Security Principles and Practices: GenAI and LLM Defense

What You’ll Learn

• Build essential GenAI and LLM security skills, from tokenization and attack surface analysis to the OWASP Top 10 for LLMs—no AI background required.
• Identify, exploit, and defend against AI-specific threats like prompt injection, jailbreaking, and RAG manipulation in hands-on labs.
• Implement practical defenses for training pipelines, inference environments, and RAG systems across enterprise settings.
• Secure advanced AI architectures, including agentic systems and reasoning models.
• Apply frameworks such as MITRE ATLAS, OWASP Top 10 for LLMs, and NIST AI RMF in real-world security operations.
• Integrate AI security into existing SOC workflows and incident response.

Business Takeaways

• Rapidly upskill cybersecurity teams to address GenAI and LLM security without prior AI experience.
• Continuous learning: new labs, modules, and recordings expand automatically during the 4-month access window.
• Gain deployable, real-world skills through Docker-based, hands-on labs.
• Improve engagement and retention with gamified learning and an integrated Learning Assistant.
• Reduce AI deployment risk and meet compliance requirements with NIST AI RMF, EU AI Act, and other standards.
• Stay current on emerging threats through ongoing curriculum updates.