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Agentic AI systems represent a significant leap forward for AI. Their ability to plan, reason, act, and adapt autonomously introduces new capabilities and, consequently, new security challenges. Traditional red teaming methods are insufficient for these complex environments.

This publication provides a detailed red teaming framework for Agentic AI. It explains how to test critical vulnerabilities across dimensions like permission escalation, hallucination, orchestration flaws, memory manipulation, and supply chain risks. Each section delivers actionable steps to support robust risk identification and response planning. 

As AI agents integrate into enterprise and critical infrastructure, proactive red teaming must become a continuous function. Security teams need to test isolated model behaviors, full agent workflows, inter-agent dependencies, and real-world failure modes. This guide enables that shift. It helps organizations validate whether their Agentic AI implementations enforce role boundaries, maintain context integrity, detect anomalies, and minimize attack blast radius.