Home Specialist skills Artificial Intelligence SEC411: AI Security Principles and Practices: GenAI and LLM Defense
SEC411: AI Security Principles and Practices: GenAI and LLM Defense
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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.
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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.
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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.
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Accelerate team readiness: Gamified labs and an integrated Learning Assistant boost engagement and retention, helping teams achieve competency faster than with traditional training.
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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.
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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.
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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.
Overview
Off the shelf (OTS)
Target Audience:
SEC411 is ideal for cybersecurity professionals seeking to understand and defend against threats introduced by Generative AI and Large Language Models.
This includes:
• Security Analysts
• Engineers
• SOC Operators
• Incident Responders
• Red Teamers
• IT professionals who want to expand their skill set to include AI system security
No prior AI or data science experience is required—only a foundation in general cybersecurity principles.
Description:
SEC411 is a living, practitioner-focused AI security course for cybersecurity professionals entering GenAI and LLM defense. No prior AI experience required.
The course includes 18+ hours of expert-led content and five hands-on labs with well over 100 tasks, including expanded coverage of Model Context Protocol (MCP) security and emerging AI attack surfaces. Unlike other OnDemand courses, the curriculum will be dynamically updated during your 4-month access window. Depending on when you enroll, you will receive new videos and you might also get new modules and lab challenges, so your training keeps pace with the rapidly evolving AI threat landscape. To facilitate this approach, this course does not have a print coursebook or a traditional PDF coursebook.
Syllabus Summary:
• Section 1: KNOW - Understanding the AI Threat Landscape
• Section 2: DEFEND – Securing the AI Lifecycle
• Section 3: DEPLOY – Integration, Autonomy, and Advanced AI
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.
Please note – data may be processed in countries with adequacy agreements in place.
Delivery method
Digital
Course duration
18 hours
Competency level
Working
