AI-Driven Ethical Hacking and Machine Learning Applications in Offensive and Defensive Cybersecurity

As cyber threats evolve in scale and complexity, ethical hacking must also advance beyond traditional approaches. This chapter explores how artificial intelligence (AI) and machine learning (ML) are revolutionizing penetration testing, from reconnaissance and vulnerability assessment to social engineering and blue teaming. It examines real-world applications, adversarial AI risks, and the ethical boundaries of automated attacks. The chapter also highlights regulatory implications and emerging trends such as explainable AI and autonomous red teaming. It provides a forward-looking perspective on how AI can responsibly augment cybersecurity practices in both offensive and defensive contexts.