Penetration Testing Using Artificial Intelligence: Methods, Tools, and Practice for the Modern Offensive Security Professional

Artificial intelligence has fundamentally transformed the practice of offensive security — not merely accelerating what penetration testers already do, but qualitatively changing how they think, plan, and execute. Penetration Testing Using Artificial Intelligence is the definitive practitioner's guide to this new era, taking the modern offensive security professional from foundational AI and machine learning concepts through every phase of the AI-augmented engagement lifecycle: reconnaissance and OSINT powered by large language models, intelligent scanning and asset discovery, ML-driven vulnerability prioritization, AI-assisted exploit development, and post-exploitation decision-making guided by autonomous agents. Spanning web, network, cloud, mobile, wireless, IoT, and OT/ICS environments, and dedicating full coverage to adversarial machine learning, LLM red teaming, generative AI-powered social engineering, and the emerging threat of autonomous offensive agents, this book equips practitioners with the tools, frameworks, techniques, and ethical grounding required to operate at the frontier of the discipline — while navigating the legal, regulatory, and professional responsibilities that come with wielding AI as an offensive instrument. Grounded in real-world case studies, aligned with MITRE ATT&CK, OWASP, NIST, and the EU AI Act, and written for security professionals who refuse to be left behind, this is not a book about the future of penetration testing — it is a field manual for the present. Read more