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Agentic AI for Offensive Cybersecurity: Build and automate smarter penetration testing workflows using AI-driven agents [Pehme köide]

  • Formaat: Paperback / softback, 412 pages, kõrgus x laius: 235x191 mm
  • Ilmumisaeg: 25-Feb-2026
  • Kirjastus: Packt Publishing Limited
  • ISBN-10: 180611447X
  • ISBN-13: 9781806114474
Teised raamatud teemal:
  • Formaat: Paperback / softback, 412 pages, kõrgus x laius: 235x191 mm
  • Ilmumisaeg: 25-Feb-2026
  • Kirjastus: Packt Publishing Limited
  • ISBN-10: 180611447X
  • ISBN-13: 9781806114474
Teised raamatud teemal:
Master offensive security with Agentic AI, MCP, and n8n. Build automated penetration testing workflows for reconnaissance, exploitation, reporting, and continuous threat intelligence.

Key Features

Build end-to-end agentic AI-driven penetration testing workflows using n8n and Model Context Protocol(MCP). Automate reconnaissance, exploitation, payload generation, and professional vulnerability reporting with agentic AI agents. Design browser-based security testing tools with MCP, and integrate continuous threat intelligence into your offensive workflows.

Book Description AI agents have moved from demos to practical tooling, especially for offensive security work where repeatability and context matter. This book shows you how to apply agentic AI to real penetration testing automation, keeping a human in the loop while speeding up reconnaissance, validation, and reporting. Youll build end-to-end workflows with n8n for reconnaissance automation, attack surface management, and repeatable testing tasks such as port scanning and PCI segmentation testing. Youll also create browser-based security testing tools using the Model Context Protocol (MCP), enabling LLM-powered agents to coordinate tooling, manage context, and assist with vulnerability analysis and documentation. The focus is hands-on practice, as youll assemble practical offensive workflows for web application testing, exploitation support, and professional pentest reporting, then extend your pipeline with threat intelligence automation, including agents that monitor CVE feeds and keep your testing aligned with emerging risk. If youre a penetration tester, red teamer, or security engineer looking to make assessments faster, more consistent, and easier to scale across engagements, this book gives you patterns that you can adapt to your environment.What you will learn

Understand agentic AI principles for offensive security Evaluate and select AI frameworks for security automation Build your first AI-driven recon workflow using n8n Automate attack surface discovery and port scanning with AI Design PCI segmentation testing workflows with n8n Build web app testing tools using MCP Automate exploitation, payload generation, and reporting Create threat intelligence agents that monitor CVE feeds

Who this book is forThis book is perfect for cybersecurity professionals, penetration testers, red teamers, CISOs, and security managers. If you're aiming to understand how AI-driven automation can enhance offensive cybersecurity workflows and vulnerability management, you'll find valuable insights and practical guidance here.
Table of Contents

Introduction to Agentic AI
AI Frameworks for Security Automation
Building Your First AI Workflow in n8n
Agentic AI for Attack Surface Management
Internal Network and PCI Segmentation Testing
Web Application Testing with Agentic AI
Exploitation, Payload Generation, and Reporting
Learning, Research, and CTI Agents
Scaling and Ethical Considerations
Orhan Yldrm is a cybersecurity expert with over nine years of hands-on experience in offensive security. He has led and contributed to high-impact penetration testing engagements for Fortune 100 companies, with a focus on securing large-scale, business-critical infrastructure. Orhan holds multiple advanced industry certifications in red teaming, web and network exploitation, and cloud security. His background spans roles such as Pentester, AppSec Engineer, and Red Teamer. A regular contributor to the cybersecurity community, he has spoken at BSides and published articles on vulnerability discovery and automation.