Overview

What if the biggest vulnerability in your AI system isn't in the code, but in the way it was built? The AI Security Developer's Playbook is the definitive guide for developers, engineers, and security professionals who are tasked with building, deploying, and defending intelligent systems. In a world where AI drives everything from critical infrastructure to financial decisions, security can no longer be an afterthought-it must be engineered from the ground up. This book arms you with actionable, hands-on strategies to secure machine learning models and implement AI-driven cyber defenses. Unlike theoretical or compliance-focused guides, this playbook translates cutting-edge research into practical engineering steps you can implement immediately. You'll learn how to: Harden models against adversarial attacks, data poisoning, and model theft. Architect secure LLM applications to resist prompt injection, jailbreaking, and data leakage. Integrate security into every phase of the AI/ML lifecycle-from data pipeline to production deployment. Leverage AI itself as a defensive tool for threat detection, anomaly hunting, and automated response. Operationalize security with frameworks like MITRE ATLAS, OWASP Top 10 for LLMs, and NIST AI RMF. Structured as a progressive framework, the book moves from foundational concepts to advanced techniques, complete with real-world case studies, tool deep dives, and ready-to-use code examples. Whether you're defending existing AI systems or building new ones, this playbook provides the proven methods, architectural patterns, and developer-first mindset needed to stay ahead in the evolving arms race of AI security. Stop treating AI security as a checklist. Start building systems that are resilient, trustworthy, and secure by design. Your role as an AI Security Developer starts here-turn the page and build with confidence.

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