AI Security

AI security is a first-class engineering discipline — this book teaches you to think like an attacker of intelligence itself, then build defenses that actually hold in production. AI systems fail differently from normal software. A database doesn't get talked into handing over its contents; an LLM does. Most security books teach you about firewalls. This one treats AI security as what it is: the discipline of protecting systems whose behavior is probabilistic, whose inputs are natural language, and whose agents can take real actions in the world. Inside you will learn: prompt injection and jailbreaks — how attackers bend LLMs, and the defenses that actually work; LLM red teaming: how to systematically break your own prompt pipelines before attackers do; RAG and vector-database security; AI agent security: tool permissions, least privilege, and stopping agents from going rogue; guardrails and monitoring for production LLM apps; data poisoning, model extraction, and supply-chain attacks; how to run a security review of an AI system your clients will pay for. You do not need a PhD in cryptography or machine learning. You need curiosity, a laptop, and the willingness to try breaking things in a sandbox before attackers break them in production. Perfect for: developers building LLM apps and AI agents, security engineers, ML engineers moving into production, founders shipping AI features, and red teamers expanding into AI.