May 2026
Intermediate
368 pages
9h 10m
English
Overview
Agentic AI for Cybersecurity: Building Autonomous Defenders and Adversaries
Unlock the power of nextgeneration AI agents to transform cybersecurity, business operations, and productivity.
Agentic AI has transformed cybersecurity and other domains with autonomous, intelligent software agents that can plan, reason, and take action. Instead of simply answering questions, these agents work like digital analysts using tools and adapting to new information, while collaborating with humans and other agents to get real work done.
Agentic AI for Cybersecurity is a practical, handson guide to building, deploying, and securing these systems. Written in plain English, the book explains how modern agentic AI frameworks (such as LangChain, LangGraph, CrewAI, and LlamaIndex) enable autonomous, multiagent systems, and how frameworks like Model Context Protocol (MCP) and agenttoagent (A2A) are creating an emerging Internet of Agents.
Through stepbystep projects and realworld case studies, readers learn how to apply agentic AI to cybersecurity defense, adversarial testing, business automation, and productivity workflows. The book also addresses critical risks, including adversarial threats, governance, and compliance. The goal is to make security a firstclass concern, not an afterthought.
Designed for both technical and nontechnical readers, this book bridges the gap between AI theory and realworld impact.
Key Features
Handson projects with practical examples for building and deploying AI agents
Covers leading agentic AI frameworks and protocols (LangChain, CrewAI, LangGraph, MCP, A2A, n8n, OpenAI Agent Builder, and more)
Securityfirst approach with dedicated coverage of adversarial threats and governance
PlainEnglish explanations with diagrams, exercises, and GitHub resources
Who This Book Is For
Cybersecurity professionals, AI engineers, developers, architects, business and technology leaders, or anyone looking to understand and apply agentic AI responsibly and effectively.
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