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

SEC411Cyber Defense, Artificial Intelligence
  • 24 Hours (Self-Paced)
Course authored by:
Seth Misenar
Seth Misenar
SEC411
Course authored by:
Seth Misenar
Seth Misenar
  • 24 CPEs

    Apply your credits to renew your certifications

  • Self-paced

    Train at your own pace from wherever you are

  • Intermediate Skill Level

    Course material is geared for cyber security professionals with hands-on experience

  • 5 Hands-On Lab(s)

    Apply what you learn with hands-on exercises and labs

Defend real-world GenAI and LLM systems with hands-on labs and practical AI security techniques. Always current. Always hands-on. Always relevant.

Course Overview

SEC411 is a living, practitioner-focused AI security course for cybersecurity professionals entering GenAI and LLM defense. No prior AI experience required.

What You’ll Learn

  • Master AI security fundamentals including tokenization, attack surface analysis, and OWASP Top 10 for LLMs.
  • Exploit and defend against prompt injection, jailbreaking, RAG manipulation, MCP security, and context hijacking across 125+ hands-on lab tasks.
  • Implement production-ready defenses for inference runtime, system prompts, and RAG applications.
  • Secure agentic workflows, autonomous systems, and reasoning models against manipulation and misuse.
  • Apply OWASP Top 10 for LLMs, MITRE ATLAS, and NIST AI RMF in real security operations scenarios.
  • Bridge traditional cybersecurity skills to AI-specific requirements and SOC integration.
  • Design defense-in-depth strategies that balance security and usability across the AI lifecycle.
  • Protect Model Context Protocol (MCP) environments by identifying attack surfaces and enforcing controls.
  • Master prompt-injection techniques from direct instruction attacks and encoding-based obfuscation to context-window manipulation and social-engineering.
  • Build a vendor-neutral detection and incident-response capability spanning prompt, retrieval, tool, and memory-based attacks, grounded in OWASP's Agentic Top 10 threat categories including Tool Misuse and Memory Poisoning.
  • Critically evaluate Anthropic's Fable 5 and Mythos 5 safety disclosures and government-driven access changes, translating a fast-moving capability and access-governance story into concrete defensive action.

Business Takeaways

  • Close critical skill gaps quickly with progressive learning paths building on existing expertise.
  • Maximize training ROI with a living curriculum that adds new modules and labs throughout 4-month access.
  • Apply learning immediately with Docker-based hands-on labs deployable in real production environments.
  • Accelerate team readiness with gamified labs and an integrated Learning Assistant for faster competency.
  • Reduce deployment risk with comprehensive OWASP Top 10 for LLMs and production security controls coverage.
  • Support compliance with NIST AI RMF, EU AI Act, and other standards connected to existing security ops.
  • Future-proof security capabilities spanning current and emerging AI threats with continuous curriculum updates.
  • Reduce response gaps with a unified monitoring and incident-response framework for the major ways untrusted content reaches AI systems.
  • Stay ahead of the frontier: SEC411's living curriculum keeps your team current on capability and access shifts like Anthropic's Fable 5/Mythos 5, not months after the fact.

Course Syllabus

Explore the course syllabus below to view the full range of topics covered in SEC411: AI Security Principles and Practices: GenAI and LLM Defense.

Section 1KNOW - Understanding the AI Threat Landscape

Build essential AI literacy for security professionals. Learn how LLMs operate, identify AI-specific attack surfaces, and develop intuition about GenAI and LLM applications. This foundation bridges traditional security experience to AI threats with hands-on exploration of tokenization security.

Section 2DEFEND – Securing the AI Lifecycle

Secure AI systems from training to runtime. Implement practical defenses for training pipelines, inference environments, and RAG systems. Master input and output filtering, guardrail implementation, and RAG-specific security controls through progressive attack and defense challenges.

Section 3DEPLOY – Integration, Autonomy, and Advanced AI

Integrate AI security into enterprise architecture and protect autonomous systems. Deploy secure LLM applications, implement robust API security, connect AI monitoring with SOC operations, and address new threats in agentic systems and reasoning models using production-ready strategies.

Things You Need To Know

Relevant Job Roles

Artificial Intelligence and Data Ethics (AIDE)

Skills Framework for the Information Age

Responsible design, development, and governance of AI and data-driven systems. Ethical principles are embedded into algorithms, models, and automated decision-making to ensure fairness, transparency, and accountability.

Explore learning path

Course Schedule and Pricing

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  • Location & instructor

    Virtual (OnDemand)

    Instructed by
    Date & Time
    OnDemand (Anytime)Self-Paced, 4 months access
    Course price
    $2,999 USD*Prices exclude applicable local taxes
    Registration Options
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SEC411: AI Security Principles and Practices: GenAI and LLM Defense | SANS Institute