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

What You'll Learn

• Master AI security fundamentals: Build essential GenAI and LLM knowledge, including tokenization security, attack surface analysis, and the OWASP Top 10 for LLMs. No prior AI background needed.
• Exploit and defend against AI-specific attacks: Practice across five hands-on labs and more than 100 tasks covering prompt injection, jailbreaking, RAG manipulation, MCP security, and context hijacking
• Implement production-ready defenses: Deploy practical security controls for inference runtime, system prompts, and RAG applications in enterprise environments.
• Secure advanced AI systems: Defend agentic workflows, autonomous systems, and reasoning models against manipulation, misuse, and emerging attack techniques.
• Apply industry frameworks effectively: Use the OWASP Top 10 for LLMs, MITRE ATLAS, and NIST AI RMF in scenarios that reflect current security operations.
• Bridge traditional security and AI: Connect your existing cybersecurity skills to AI-specific requirements, integrating AI security with SOC operations and incident response.
• Build adaptive AI security programs: Design defense-in-depth strategies that balance security and usability throughout the entire AI lifecycle, from training to deployment.
• Secure AI integrations and protocols: Protect Model Context Protocol (MCP) environments by identifying attack surfaces, enforcing controls, and defending real-world AI system interactions.

Business Takeaways

• Close critical skill gaps quickly: Upskill your cybersecurity teams to handle GenAI and LLM security challenges using progressive learning paths that build on existing expertise. No prior AI background needed.
• Maximize training ROI with a living curriculum: New modules, labs, and recordings are added automatically throughout the 4-month access period, providing continuous content expansion unique in the field.
• Apply learning immediately: Docker-based hands-on labs remove technical barriers and deliver practical skills that teams can deploy in real production environments right away.
• Accelerate team readiness: Gamified labs and an integrated Learning Assistant boost engagement and retention, helping teams achieve competency faster than with traditional training.
• Reduce deployment risk: Comprehensive coverage of the AI attack surface, the OWASP Top 10 for LLMs, and production security controls ensures organizational deployments are protected with confidence.
• Support compliance and governance: Align AI security practices with the NIST AI Risk Management Framework, EU AI Act, and other industry standards while connecting efforts to existing security operations.
• Future-proof security capabilities: Training spans the full spectrum of AI threats, from current prompt injection to emerging agentic risks, with continuous updates as new challenges develop.