Offensive LLM Security (Paperback)
Language: English
Published by Notion Press, 2026
- Softcover
- New

Seller: CitiRetail, Stevenage, United KingdomCitiRetail
AbeBooks seller since June 29, 2022
Condition: New
US$ 46.18
Quantity: 1 available
Add to basketItem description from seller
Paperback. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…
Seller Inventory # 9798905407635
- Title
- Offensive LLM Security (Paperback)
- Author
- Anand Patil
- Publisher
- Notion Press
- Publication year
- 2026
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 13
- 9798905407635
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.
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CitiRetail
Stevenage, United Kingdom
AbeBooks seller since June 29, 2022
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