• views: 72
• date: 25 August 2026
• posted by: AD-TEAM

What you'll learn

Explain the OWASP Agentic Security Top 10 and how each risk appears in AI agents.

Map agent attacks across goal hijack, tools, identity, memory, supply chain, and multi-agent systems.

Evaluate real enterprise scenarios and identify the trust boundary that fails.

Design layered defenses and governance controls for safer agentic applications.

Requirements

Basic familiarity with AI agents, APIs, or application security is helpful, but no prior agentic security experience is required.

Description

"This course contains the use of artificial intelligence."AI agent security is quickly becoming a core skill for engineers, architects, and security leaders building autonomous systems. This course teaches agentic AI security through the OWASP Top 10 for Agentic Applications, using real attack scenarios, technology maps, and practical defense patterns you can apply to AI agents in production.You will learn how prompt injection, goal hijack, tool misuse, identity and privilege abuse, supply chain compromise, memory poisoning, insecure inter-agent communication, cascading failures, human trust exploitation, and rogue agent behavior appear in real systems. We also cover guardrails, secure architecture, runtime validation, least privilege, memory controls, and governed autonomy for agentic AI systems.Each module connects theory to enterprise reality. You will walk through realistic attack chains in customer support, finance, DevOps, healthcare, retail, and multi-agent automation. Then you will break down the terminology, trust boundaries, control points, and design decisions that prevent the same failure in production.By the end of the course, you will be able to explain the OWASP agentic AI risk model, recognize how AI agent security issues show up in live workflows, and evaluate the guardrails needed to build safer autonomous applications.This course is designed for security engineers, AI engineers, architects, product leaders, and technical managers who want a practical framework for securing AI agents and agentic applications.

Security engineers, AI engineers, architects, technical product leaders, and managers building or reviewing agentic systems.





   
   
   

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