This book discusses in detail the AI-driven cyber threat landscape, including inherent AI threats and risks that exist in Large Language Models (LLMs), Generative AI Applications, and AI infrastructure. The book highlights hands-on technical approaches to detect security flaws in AI systems and applications utilizing the intelligence gathered from real-world case studies. Lastly, the book presents a very detailed discussion of the defense mechanisms and practical solutions to secure LLMs, GenAI applications, and AI infrastructure.  The chapters are structured with a granular framework, starting with the AI concepts, followed by practical assessment techniques based on real-world intelligence, and concluding with required security defenses.
By the end of this book the reader will understand: 
·        The practical concepts and intelligence required to build threat models and assessing security posture of LLMs, GenAI applications and AI infrastructure
·        The AI threat landscape by learning from real-world examples covering different ways attackers abuse AI systems to trigger cyberattacks
·        The intrinsic details of adversarial attacks targeting AI systems
·        The defense mechanisms required to secure LLMs, GenAI applications and AI infrastructure
·        The concepts of safe AI including compliance and trust