The attack surface for your enterprise just expanded by every prompt your users type. Generative AI doesn't just change what software can do - it changes how it gets compromised. Prompt injection, poisoned retrieval pipelines, data-leaking agents, and unconstrained model outputs are not theoretical threats. They are happening in production systems today, and traditional security controls were never built to stop them. LLM Firewalls: Securing AI Systems in the Age of Generative Intelligence is the definitive practitioner's guide to closing that gap. Written by an enterprise security architect with deep experience securing AI infrastructure at scale, this book builds a rigorous, end-to-end security framework for the full lifecycle of an LLM interaction — from the first prompt to the last autonomous action. You won't find vendor marketing or surface-level overviews here. You'll find architecture decisions, defense patterns, and hard-won operational insight that translate directly into production-grade AI systems. What you'll master: Prompt Injection — Direct & Indirect: Understand how attackers weaponize inputs, hijack retrieval sources, and manipulate model behavior — and how to reduce blast radius at the architecture level - RAG Pipeline Hardening: Discover how knowledge retrieval becomes an exfiltration path, and how to secure chunking, embedding, and retrieval without destroying utility - Output Security: Apply DLP, schema enforcement, and structured validation to ensure model responses never leak what they shouldn't - Agent & Tool Governance: Constrain autonomous agents with least-privilege principles, human-in-the-loop approvals, and scope boundaries that hold under adversarial pressure - Enterprise Integration: Embed LLM security into your existing Zero Trust architecture, SIEM/SOC workflows, and compliance programs — without building a parallel security stack - Maturity Measurement: Assess where your AI security posture stands today and build a defensible, board-presentable roadmap for where it needs to go Why this book is different: Most AI security content stops at awareness. This book starts there and goes all the way to implementation. Every chapter connects threat model to control design to operational workflow - so security leaders, architects, and engineers can all work from the same playbook. Whether you are deploying your first RAG application or governing a portfolio of autonomous agents across a global enterprise, this book gives you the mental models, technical controls, and governance structures to do it defensibly. Generative AI is not going to slow down. Your security posture needs to move faster. For CISOs, security architects, AI engineers, platform teams, and governance professionals building the next generation of enterprise AI — safely.