{ "item_title" : "Offensive LLM Security", "item_author" : [" Anand Patil "], "item_description" : "LLM-powered applications are not magic-they are software systems built from prompts, retrieval pipelines, tools, agents, APIs, and trust boundaries. Each layer creates new opportunities for attackers.Offensive LLM Security is a practical guide for pentesters, bug-bounty researchers, application-security engineers, and developers who want to understand how modern AI applications fail. It covers direct and indirect prompt injection, jailbreaking, system-prompt extraction, insecure output handling, RAG poisoning, cross-tenant data leakage, excessive agency, MCP attacks, AI supply-chain risks, and model-serving infrastructure.Through hands-on labs, attack methodologies, measurement techniques, and complete worked engagements, readers learn how to trace attacker-controlled input through an LLM system to a privileged sink and demonstrate meaningful impact.Rather than treating AI security as a collection of clever prompts, this book applies proven application-security thinking to the full LLM stack-helping readers identify, reproduce, measure, report, and remediate real vulnerabilities.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/79/890/540/9798905407635_b.jpg", "price_data" : { "retail_price" : "35.99", "online_price" : "35.99", "our_price" : "35.99", "club_price" : "35.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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