★★★★★
Highly Rated by InfoSec Pros

Build the Future of
Offensive Security

A practical, hands-on blueprint for security professionals, ethical hackers, and DevSecOps engineers ready to design, orchestrate, and deploy intelligent AI agents that discover, validate, and report web vulnerabilities—automatically.

Automated Penetration Testing Cover

Why Autonomous AI Is Reshaping Penetration Testing

Move beyond static scanners. Deploy reasoning agents.

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Cut False Positives with AI Validation

Use LLM-powered reasoning and Retrieval-Augmented Generation to separate real threats from scanner noise with context-aware precision.

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Slash Pentest Overhead

Deploy agents that reason, plan, execute, and report—freeing your team to focus on high-impact analysis instead of repetitive scanning.

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Embed Security in CI/CD

Automate web application testing inside your pipelines for continuous, proactive defense without slowing down delivery.

Scale with Multi-Agent Orchestration

Build collaborative CrewAI systems where specialized agents work together to tackle complex attack surfaces at enterprise scale.

Inside the 11-Chapter Blueprint

Systematic execution from foundation to deployment.

Chapter 1

The Autonomous Security Imperative

Understand why AI-driven offensive security is becoming essential and how autonomous agents are redefining the pentest lifecycle.

Chapter 2

LLM Foundations for Security Engineers

Master the core concepts of Large Language Models and how they apply to cybersecurity reasoning and decision-making.

Chapter 3

Prompt Engineering for Precision Attacks

Learn how to craft precise, safe, and effective prompts that guide AI agents through offensive security tasks.

Chapter 4

Tool-Calling and API Orchestration

Build agents that dynamically call security tools, APIs, and scripts to execute real-world attacks and reconnaissance.

Chapter 5

RAG for Context-Aware Testing

Implement RAG pipelines that ground agent decisions in relevant vulnerability data, documentation, and prior findings.

Chapter 6

Multi-Agent Systems with CrewAI

Design collaborative agent crews where planners, executors, validators, and reporters work together seamlessly.

Chapter 7

Integrating with CI/CD Pipelines

Embed autonomous security testing into DevOps workflows for continuous, automated application hardening.

Plus 4 more advanced chapters covering guardrails, deployment, and future trends...

System Query / FAQ

What specific AI technologies does this book cover? +
The book covers Large Language Models, prompt engineering, tool-calling agents, APIs, Retrieval-Augmented Generation, CrewAI for multi-agent orchestration, CI/CD integration, and production deployment patterns.
Is this book for red team or blue team professionals? +
Both. While the focus is offensive automation, the guardrails, validation techniques, and CI/CD integration directly strengthen defensive security postures.
Do I need to be a Python expert? +
A foundational understanding of Python is recommended, as the book focuses on building and orchestrating AI agents using Python-based frameworks like CrewAI and LangChain.

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