{ "item_title" : "AI Security Operations Guide", "item_author" : [" Ruvian Thalcor "], "item_description" : "AI systems do not fail like traditional software. They do not crash, throw clear errors, or politely alert your SOC that something is wrong. They improvise. They drift. They confidently do the wrong thing while insisting everything is fine. And by the time most teams realize something is off, the incident has already happened.This book exists for that exact moment.AI Security Operations Guide is a practical, operator-focused guide to securing AI systems after they go live. It is not about theory, ethics, or abstract risk. It is about what actually breaks in production, how to see it early, and how to respond without panic.Okay, it is deployed. Now what?Inside, every core operational challenge gets a full, practical treatment:Building an AI-Aware SOC - how to establish clear ownership, escalation paths, and team structure for AI security operations that did not exist in your organization last yearPrompt and Output Observability - how to design meaningful logging for prompts, completions, memory retrievals, and agent decisions without drowning in noisePrompt Injection and Jailbreak Detection - how to identify active exploitation attempts in live systems, distinguish attacks from benign edge cases, and tune detection without alert fatigueAutonomous Agent Monitoring - how to watch agents for tool abuse, privilege escalation, goal drift, and persistence behaviors that traditional monitoring was never designed to catchCost-Based Denial of Service Detection - how to identify silent financial abuse, resource exhaustion attacks, and API cost manipulation before they become billing disastersIncident Response Runbooks - practical containment strategies, rollback procedures, and escalation playbooks built specifically for LLM and agent security incidentsThreat Hunting Across AI Systems - how to proactively search for compromise, misuse, and behavioral anomalies instead of waiting for obvious alerts that may never comeAI Security Metrics and KPIs - how to measure what actually matters in AI operations and report security posture to engineers, leadership, and compliance stakeholders in language that landsAI Security Operations Guide is Book 9 in the series:The AI Security & Hacking Bible: Protect and Exploit LLMs and Autonomous AgentsEarlier titles - LLM Security in Practice, AI Threat Modeling, The LLM Top 10 Security Guide, Red Teaming LLMs, How AI Agents Work, Hardening AI Agents, The AI Agent Attacker's Playbook, and Building Bulletproof AI - cover how AI systems are built, attacked, and hardened. This book is where everything meets the real world. It is the operational backbone that ties the entire series together. 10 Real AI Security Incidents follows with the forensic perspective - and every case study in that volume starts with the monitoring and response gaps this book teaches you to close.This book is for you if you are a:SOC analyst or security operations engineer suddenly responsible for AI system monitoringSecOps or MLOps professional building detection and response capabilities for LLM infrastructureAppSec engineer extending existing security operations practices into AI and agent systemsPlatform engineer who deployed an AI system and now needs to know if it is behavingEngineering leader who has inherited responsibility for AI security and needs an operational starting pointAI systems are already in production. The only question is whether you are watching them closely enough.This book helps you do exactly that.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/79/818/479/9798184796567_b.jpg", "price_data" : { "retail_price" : "47.99", "online_price" : "47.99", "our_price" : "47.99", "club_price" : "47.99", "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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