Agentic AI for Cybersecurity: Building Autonomous Defenders and Adversaries

Agentic AI for Cybersecurity: Building Autonomous Defenders and Adversaries

Unlock the power of next-generation 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, hands-on 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, multi-agent systems, and how frameworks like Model Context Protocol (MCP) and agent-to-agent (A2A) are creating an emerging Internet of Agents.

Through step-by-step projects and real-world 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 first-class concern, not an afterthought.

Designed for both technical and non-technical readers, this book bridges the gap between AI theory and real-world impact.

Key Features

• Hands-on 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)
• Security-first approach with dedicated coverage of adversarial threats and governance
• Plain-English 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.