{"product_id":"generative-ai-security-engineering-protect-llm-applications-rag-pipelines-and-ai-agents-with-secure-architecture-and-production-ready-defense-strat-9798249331313","title":"Generative AI Security Engineering: Protect LLM Applications, RAG Pipelines, and AI Agents with Secure Architecture and Production-Ready Defense Strat","description":"\u003cp\u003e • Author(s): Ralf Kohl\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Artificial Intelligence - Generative AI\u003c\/p\u003e\u003cp\u003e\u003cb\u003eGenerative AI Security Engineering: Protect LLM Applications, RAG Pipelines, and AI Agents with Secure Architecture and Production-Ready Defense Strategies\u003c\/b\u003e\u003cbr\u003eYour LLM application works.\u003cbr\u003eBut is it secure under real-world pressure?\u003cbr\u003eGenerative AI is no longer experimental. Large language models now power enterprise search, customer support automation, internal copilots, analytics pipelines, and autonomous AI agents connected to live systems. They access proprietary data. They retrieve dynamic context. They generate outputs that influence decisions and trigger downstream actions.\u003cbr\u003eWhen these systems fail, they fail at scale.\u003cbr\u003ePrompt injection can override trusted instructions.\u003cbr\u003eRAG pipelines can expose confidential data through retrieval leakage.\u003cbr\u003eAI agents can invoke tools beyond their intended authority.\u003cbr\u003eInsufficient monitoring can allow subtle anomalies to evolve into major security incidents.\u003cbr\u003ePerformance alone is not production readiness. Security architecture is.\u003cbr\u003e\u003cb\u003eGenerative AI Security Engineering\u003c\/b\u003e is a practical, production-focused blueprint for protecting LLM applications, retrieval-augmented generation (RAG) pipelines, and AI agents with deterministic control and layered defense strategies. This book moves beyond high-level safety discussions and into real engineering discipline. It shows you how to design containment around probabilistic models so your systems remain powerful without becoming unpredictable liabilities.\u003cbr\u003eYou will learn how to: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003ePrevent prompt injection and semantic manipulation attacks\u003c\/li\u003e\n\u003cli\u003eHarden RAG pipelines against data poisoning and unauthorized retrieval\u003c\/li\u003e\n\u003cli\u003eEnforce metadata-scoped access control in vector databases\u003c\/li\u003e\n\u003cli\u003eSeparate model reasoning from execution authority in AI agents\u003c\/li\u003e\n\u003cli\u003eImplement structured output validation and policy enforcement\u003c\/li\u003e\n\u003cli\u003eDesign multi-stage verification and risk scoring systems\u003c\/li\u003e\n\u003cli\u003eBuild safe-state transitions and fail-closed containment mechanisms\u003c\/li\u003e\n\u003cli\u003eDeploy structured logging, anomaly detection, and SIEM\/SOAR integration\u003c\/li\u003e\n\u003cli\u003eEmbed AI security into DevSecOps workflows and enterprise governance frameworks\u003c\/li\u003e\n\u003c\/ul\u003eInstead of reacting to incidents after deployment, you will design systems that anticipate failure modes and contain them by architecture. The book presents clear patterns for trust boundary definition, inference validation, action authorization, and runtime monitoring-principles that apply whether you are using OpenAI APIs, enterprise LLM platforms, or custom-built generative systems.\u003cbr\u003eWritten for engineers, architects, security practitioners, and technical leaders, this guide treats generative AI security as a first-class engineering discipline. It reflects the reality of production environments where compliance, confidentiality, and operational stability cannot be compromised.\u003cbr\u003eModel intelligence attracts attention. Secure architecture sustains trust.\u003cbr\u003eIf you are building LLM-powered applications, retrieval-augmented generation systems, or autonomous AI agents in production, this book provides the production-ready defense strategies required to operate safely at scale.\u003cbr\u003eDesign with containment in mind.\u003cbr\u003eDeploy with confidence.\u003cbr\u003eBuild generative AI systems that are not only intelligent, but resilient under pressure.","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":47569099554967,"sku":"9798249331313","price":2916.0,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798249331313.webp?v=1774873137","url":"https:\/\/atlanticbooks.com\/products\/generative-ai-security-engineering-protect-llm-applications-rag-pipelines-and-ai-agents-with-secure-architecture-and-production-ready-defense-strat-9798249331313","provider":"Atlantic Books","version":"1.0","type":"link"}