{"product_id":"jailbreaking-llms-von-priyanka-neelakrishnan","title":"Jailbreaking LLMs","description":"\n                                \n                \n                \u003cp\u003eLarge Language Models (LLMs) are rapidly transforming how enterprises operate, powering customer support, internal assistants, automated workflows, search, analytics, and decision-making systems. But as organizations adopt AI at scale, they are also introducing a new and expanding attack surface. Jailbreaking LLMs explores how attackers manipulate AI systems through prompt injection, jailbreaks, adversarial inputs, data poisoning, context manipulation, retrieval attacks, and unsafe tool usage to bypass safeguards, leak sensitive data, and influence AI behavior in unexpected ways. \u003c\/p\u003e\n                                \n                \n                \u003cp\u003e \u003c\/p\u003e\n                                \n                \n                \u003cp\u003eThis book provides a practical guide to understanding, testing, and defending enterprise AI systems in the real world. Through real attack scenarios, security frameworks, red-teaming methodologies, governance strategies, and defensive architecture patterns, readers will learn how to build secure, resilient, and enterprise-ready LLM deployments. Covering everything from RAG security and agentic systems to incident response, AI governance, runtime monitoring, and future attack trends, this book connects AI innovation with modern cybersecurity practices. \u003c\/p\u003e\n                                \n                \n                \u003cp\u003eWhat you will learn \u003c\/p\u003e\n                                \n                \n                \u003cul\u003e\n                                        \n                    \n                    \u003cli\u003e\n                                                \n                        \n                        \u003cp\u003eUnderstand how LLM jailbreaks, prompt injection, and adversarial attacks work \u003c\/p\u003e\n                                                \n                    \n                    \u003c\/li\u003e\n                                        \n                \n                \u003c\/ul\u003e\n                                \n                \n                \u003cul\u003e\n                                        \n                    \n                    \u003cli\u003e\n                                                \n                        \n                        \u003cp\u003eIdentify vulnerabilities across enterprise AI systems, RAG pipelines, agents, and APIs \u003c\/p\u003e\n                                                \n                    \n                    \u003c\/li\u003e\n                                        \n                \n                \u003c\/ul\u003e\n                                \n                \n                \u003cul\u003e\n                                        \n                    \n                    \u003cli\u003e\n                                                \n                        \n                        \u003cp\u003eDesign and deploy secure, enterprise-ready LLM architectures \u003c\/p\u003e\n                                                \n                    \n                    \u003c\/li\u003e\n                                        \n                \n                \u003c\/ul\u003e\n                                \n                \n                \u003cul\u003e\n                                        \n                    \n                    \u003cli\u003e\n                                                \n                        \n                        \u003cp\u003e Implement monitoring, logging, detection, and incident response workflows for AI systems \u003c\/p\u003e\n                                                \n                    \n                    \u003c\/li\u003e\n                                        \n                \n                \u003c\/ul\u003e\n                                \n                \n                \u003cul\u003e\n                                        \n                    \n                    \u003cli\u003e\n                                                \n                        \n                        \u003cp\u003eApply red-teaming and defensive testing strategies to evaluate LLM security \u003c\/p\u003e\n                                                \n                    \n                    \u003c\/li\u003e\n                                        \n                \n                \u003c\/ul\u003e\n                                \n                \n                \u003cul\u003e\n                                        \n                    \n                    \u003cli\u003e\n                                                \n                        \n                        \u003cp\u003eBuild governance, compliance, and ethical AI controls into enterprise deployments \u003c\/p\u003e\n                                                \n                    \n                    \u003c\/li\u003e\n                                        \n                \n                \u003c\/ul\u003e\n                                \n                \n                \u003cul\u003e\n                                        \n                    \n                    \u003cli\u003e\n                                                \n                        \n                        \u003cp\u003eUnderstand emerging AI attack trends and future cybersecurity risks \u003c\/p\u003e\n                                                \n                    \n                    \u003c\/li\u003e\n                                        \n                \n                \u003c\/ul\u003e\n                                \n                \n                \u003cp\u003e  \u003c\/p\u003e\n                                \n                \n                \u003cp\u003eWho this book is for \u003c\/p\u003e\n                                \n                \n                \u003cp\u003eThis book is for cybersecurity professionals, AI\/ML engineers, enterprise architects, security analysts, SOC teams, IT leaders, and technical decision-makers responsible for building, deploying, or securing AI-powered systems. It is also valuable for practitioners who want to better understand the security, governance, and operational challenges that come with adopting Large Language Models in enterprise environments. \u003c\/p\u003e\n                                \n            \n            \u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9798868829574\"\u003e\u003ch3\u003eProtecting the Future of Enterprise Security\u003c\/h3\u003e\u003c\/div\u003e","brand":"Autorenwelt Shop","offers":[{"title":"Softcover - 9798868829574","offer_id":58016027148613,"sku":"9798868829574","price":64.19,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0940\/0622\/files\/8dd88016-399d-46d2-99f3-34e7b64f97fa.jpg?v=1782019425","url":"https:\/\/shop.autorenwelt.de\/products\/jailbreaking-llms-von-priyanka-neelakrishnan","provider":"Autorenwelt Shop","version":"1.0","type":"link"}