This eBook provides a deep technical analysis of the unique security risks introduced by agentic AI systems. It explains how AI agents expand the attack surface beyond code into prompts, reasoning chains, memory, and external tool execution, particularly through Model Context Protocol (MCP). The document details attack techniques such as prompt injection, tool poisoning, shadowing, and capability drift that manipulate agent behavior without exploiting traditional vulnerabilities. It introduces a five-layer MCP hardening framework and a practical 90-day roadmap covering identity controls, version pinning, runtime validation, observability, and human-in-the-loop approvals. The guide emphasizes that securing AI agents requires governing behavior and reasoning, not just infrastructure.

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