Nyhet

Agentic AI for Cybersecurity

Building Autonomous Defenders and Adversaries

AvOmar Santos

Häftad, Engelska, 2026

358 kr

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2026-07-29
Mått:188 x 231 x 20 mm
Vikt:610 g
Format:Häftad
Språk:Engelska
Antal sidor:368
Upplaga:1
Förlag:Pearson Education
ISBN:9780135589854

Utforska kategorier

Nätverk och kommunikation inom Data och IT
Artificiell intelligens inom Data och IT

Mer om författaren

Omar Santos, a cybersecurity leader and Distinguished Engineer at Cisco, is renowned for his expertise in ethical hacking, vulnerability research, AI security, and incident response. He has led the DEF CON’s Red Team Village, co-chaired the Coalition of Secure AI (CoSAI), and is a prolific author. Omar's contributions have significantly advanced technology and global security standards.

Innehållsförteckning

Introduction.. . . . . . . . . . . . . . . xviiPart I Foundations and Core TechnologiesChapter 1 Foundations of Agentic AI Systems. . . . . . . . . 1Reflecting and Defining the Shift.. . . . . . . . . . 2The Anatomy of a Modern AI Agentic Infrastructure.. . . . . . 9Summary. . . . . . . . . . . . . . 13Review Questions.. . . . . . . . . . . . . 15Answers to Review Questions. . . . . . . . . . 17Chapter 2 Retrieval-Augmented Generation (RAG), Agentic RAG, and Model Context Protocol (MCP).. . . . . . . . . . 19A Recap of Retrieval-Augmented Generation (RAG) and Agentic RAG. . . 20Vector Databases and Embedding Models. . . . . . . . 21A Deep Dive into the Model Context Protocol (MCP).. . . . . . 42Summary. . . . . . . . . . . . . . 46Review Questions.. . . . . . . . . . . . . 47Answers to Review Questions. . . . . . . . . . 50End-of-Chapter Projects.. . . . . . . . . . . 51Chapter 3 Protocols for the Internet of Agents.. . . . . . . . . 55The Agent2Agent (A2A) Protocol . . . . . . . . . . 55The Agent Communication Protocol (ACP). . . . . . . . 64Agent Name Service (ANS): A Secure Universal Directory. . . . . 66AGNTCY: Building the Foundational Stack for an “Internet of Agents”.. . . 69Summary. . . . . . . . . . . . . . 71Review Questions.. . . . . . . . . . . . . 72Answers to Review Questions. . . . . . . . . . 74Chapter 4 Orchestration with LangChain, LangGraph, and LlamaIndex. . . 75Introducing LangChain. . . . . . . . . . . . 76Using LangGraph Agent Workflows.. . . . . . . . . 78Introducing LlamaIndex.. . . . . . . . . . . 87Choosing Your Framework.. . . . . . . . . . . 89Summary. . . . . . . . . . . . . . 91Review Questions.. . . . . . . . . . . . . 92Answers to Review Questions. . . . . . . . . . 94Chapter 5 Exploring CrewAI, n8n, Apache Airflow, OpenAI Agent Builder, and Other Agentic Frameworks.. . . . . . . . . . 95CrewAI: The Power of Role-Based Collaboration. . . . . . . 96n8n: Visual Workflow and Low-Code Automation. . . . . . 101Apache Airflow.. . . . . . . . . . . . . 116Langflow: Visual Orchestration and Deployment for GenAI.. . . . 121The OpenAI Agent Platform.. . . . . . . . . . 122Summary. . . . . . . . . . . . . . 125Chapter Review Questions.. . . . . . . . . . . 126Answers to Review Questions. . . . . . . . . . 128Part II Applications and SecurityChapter 6 The Architect’s Cockpit: AI-Powered IDEs and Coding Agents.. . . 131Defining the Modern AI Coding Agent. . . . . . . . 131A Comparative Analysis of Leading AI Coding Agents.. . . . . 139Establishing Enterprise-Grade Evaluation Criteria. . . . . . 154Project CodeGuard: Don’t Let Your AI Agents Introduce Security Vulnerabilities.. 156Summary. . . . . . . . . . . . . . 158Chapter Review Questions.. . . . . . . . . . . 159Answers to Review Questions. . . . . . . . . . 161Project 6-1: Using Project CodeGuard to Create More Secure Code. . . 162Chapter 7 Building an Autonomous SOC Analyst. . . . . . . . 165The Crisis in Modern Security Operations. . . . . . . . 166Anatomy of an Autonomous SOC Analyst.. . . . . . . . 167Building the Foundation: Technical Implementation.. . . . . . 171Advanced Implementation Patterns. . . . . . . . . 197Summary. . . . . . . . . . . . . . 210Chapter Review Questions.. . . . . . . . . . . 211Answers to Review Questions. . . . . . . . . . 212Project 7-1: Building Your Own Autonomous SOC Analyst. . . . . 213Chapter 8 Agentic Penetration Testing, Red Teaming, and Bug Bounties. . . 215Real-Life Attacks.. . . . . . . . . . . . . 216Case Study: Using LangGraph and n8n for Cyberattacks and Espionage.. . 218Building Penetration Testing Agents with LangChain and LangGraph. . 221Agent Skills for Offensive Security.. . . . . . . . . 240Summary. . . . . . . . . . . . . . 251Chapter Review Questions.. . . . . . . . . . . 252Answers to Review Questions. . . . . . . . . . 254Chapter 9 AI Agents for Business Leaders and Project Managers.. . . . 255Understanding AI Agents from a Cybersecurity Leadership Perspective.. . 256Strategic Applications of AI Agents for Cybersecurity Leaders.. . . . 256AI Agents for Cybersecurity Project Management.. . . . . . 260Case Studies.. . . . . . . . . . . . . 262Summary. . . . . . . . . . . . . . 265Chapter Review Questions.. . . . . . . . . . . 266Answers to Review Questions. . . . . . . . . . 267Chapter 10 Securing Agentic AI Systems. . . . . . . . . . 269The Unique Security Challenges of AI Systems. . . . . . . 269The Coalition for Secure AI (CoSAI).. . . . . . . . . 273The CoSAI Risk Map: Understanding AI Security Risks.. . . . . 273Security Controls for AI Systems.. . . . . . . . . . 281AI Supply Chain Security. . . . . . . . . . . 289AI Incident Response Framework.. . . . . . . . . 293Agentic AI Architecture Security Patterns. . . . . . . . 298Provider Versus Consumer Responsibilities. . . . . . . . 301Regulatory and Compliance Considerations. . . . . . . 303Case Studies and Lessons Learned.. . . . . . . . . 304MITRE ATLAS.. . . . . . . . . . . . . 306OWASP Top 10 for Agentic Applications. . . . . . . . 308The MAESTRO Threat Modeling Framework.. . . . . . . 312Summary. . . . . . . . . . . . . . 326Chapter Review Questions.. . . . . . . . . . . 327Answers to Review Questions. . . . . . . . . . 329End-of-Chapter Exercises.. . . . . . . . . . . 332 9780135589854, TOC, 4/22/26