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What Makes This Book Different?
AI security is not just about understanding cyber threats-it is about knowing where AI systems can fail, how attackers can exploit those weaknesses, and which defenses can reduce the risk. This book connects the full security picture, from protecting training data and models to defending against prompt injection, securing RAG systems, restricting AI agents, and protecting APIs and deployment environments.
Rather than leaving you with a list of threats to memorize, it shows you how to think like a security-minded AI practitioner. Through practical examples, Python-based exercises, threat modeling, and defensive techniques, you'll learn to identify vulnerabilities, choose appropriate safeguards, and test whether those safeguards work. The focus is on understanding the attack, locating the weakness, applying the defense, and verifying the result-so you can turn AI security knowledge into practical skills, even if you're just getting started.
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