Agentic AI - Risk and Cybersecurity Masterclass 2025

Übersicht

Learn the Cyber security risks around AI Agents and Agentic AI and how to mitigate them What you'll learn:

How Agentic AI Is A Game Changer For Risk And SecurityHow Agentic AI WorksWhat Are The Unique Risks That Agentic AI IntroducesHow To Mitigate Agentic AI RisksHow To Threat Model Agentic AI Systems Agentic AI represents the next evolution of artificial intelligence—systems that can autonomously make decisions, plan actions, and interact with the world with minimal human intervention. As AI becomes increasingly autonomous, new risks and security challenges emerge that go beyond traditional cybersecurity concerns.The "Agentic AI Risk and Cybersecurity Masterclass" is a comprehensive course designed to provide a deep understanding of agentic AI technologies, their unique risk landscape, and the best practices for securing these intelligent systems.This course explores the principles, components, and security considerations of Agentic AI, equipping you with the knowledge to assess, mitigate, and defend against emerging AI threats.What You Will LearnFundamental principles and architecture of Agentic AI systemsUnderstanding the risk landscape in autonomous AI and its implicationsSecurity threats unique to Agentic AI, including AI autonomy risks, adversarial manipulation, and decision-based attacksHow prompt injections and model exploitation attacks evolve in an Agentic AI contextStrategies for designing secure Agentic AI systems with ethical safeguards and risk mitigation controlsCompliance and governance frameworks for Agentic AI cybersecurityCourse OutlineIntroduction to Agentic AIWhat is Agentic AI?How does it differ from Generative AIWhy security in Agentic AI is criticalRisks in Agentic AIOverview of the Agentic AI risk landscapeThreat modeling Agentic AI systemsCase Study of Threat Modeling Agentic AIsystems Security in Agentic AICreating a Security Framework For Agentic AIThreat vectors and attack techniques against autonomous AIHijacking attacks, data poisoning, and malicious automationBest practices for hardening Agentic AI models and deploying AI security frameworksWho Should Take This CourseThis course is ideal for individuals looking to understand and mitigate the cybersecurity risks associated with autonomous AI systems, including:

AI engineers & researchersCybersecurity professionalsData Scientists & AI Ethics specialistsIT Managers & risk professionalsBusiness leaders exploring Agentic AI adoptionPre-requisites Basic understanding of AI and cybersecurity concepts is recommended, but no prior knowledge of Agentic AI is required.InstructorTaimur Ijlal is a multi-award-winning cybersecurity leader with over 20+ years of global experience in cyber risk management, AI security, and IT governance.

He has been recognized with industry accolades such as CISO of the Year, CISO Top 30, and Most Outstanding Security Team.Taimur’s cybersecurity and AI courses have thousands of students worldwide, and his work has been featured in ISACA Journal, CIO Magazine Middle East, and multiple AI security publications. His books on AI Security and Cloud Computing have ranked as #1 new releases on Amazon.Join this course to stay ahead of the rapidly evolving landscape of Agentic AI Risk and Cybersecurity!

Lehrplan

• Introduction to Agentic AI
What is Agentic AI?
How does it differ from Generative AI?
Why security in Agentic AI is critical
• Risks in Agentic AI
Overview of the Agentic AI risk landscape
Threat modeling Agentic AI systems
Case Study of Threat Modeling Agentic AI systems
• Security in Agentic AI
Creating a Security Framework For Agentic AI
Threat vectors and attack techniques against autonomous AI
Hijacking attacks
Data poisoning
Malicious automation
Best practices for hardening Agentic AI models and deploying AI security frameworks
• Understanding the Risk Landscape in Autonomous AI
Security threats unique to Agentic AI
AI autonomy risks
Adversarial manipulation
Decision-based attacks
How prompt injections and model exploitation attacks evolve in an Agentic AI context
• Designing Secure Agentic AI Systems
Strategies for secure design with ethical safeguards
Risk mitigation controls
Compliance and governance frameworks for Agentic AI cybersecurity
• Conclusion
Emerging trends in Agentic AI risk and cybersecurity
Future directions and research areas in securing autonomous AI systems

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Unterrichtet von

Taimur Ijlal | Award winning cybersecurity leader and instructor

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Fachgebiete

Computer Science