Advanced Threat Modeling and Red Teaming for Agentic AI Systems : Identify, Simulate, and Defend Against Real-World Attacks on AI Agents, Multi-Agent Systems, and Enterprise AI Platforms
Language: English
Published by Independently Published Jun 2026, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
US$ 46.38
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Add to basketItem description from seller
Neuware - How do you secure an application that can rewrite its own execution logic at runtime As organizations rapidly deploy autonomous AI agents with direct write access to database engines, internal networks, and cloud infrastructure, traditional perimeter defense models fall short. When your software moves from deterministic code to probabilistic reasoning loops, how do you stop an adversary from hijacking your entire enterprise platform Advanced Threat Modeling and Red Teaming for Agentic AI Systems provides the definitive, production-first blueprint to secure non-deterministic software deployments. This comprehensive technical guide skips basic introductory concepts to deliver hard-hitting offensive engineering strategies, automated vulnerability testing pipelines, and zero-trust defensive hardening patterns. It addresses the unique architectural realities of modern multi-agent systems, shifting your security posture from reactive prompt filtering to code-enforced, continuous validation across your entire cluster fabric.What advantages will you gain by engineering your security framework from the ground up This manual equips platform architects, security engineers, and DevSecOps teams with the exact technical skills required to build an automated, self-healing defensive lifecycle.By implementing the production-grade methodologies detailed inside, you will acquire the skills to: - Build stateful autonomous red team agents to programmatically simulate complex, multi-turn adversarial cascades.- Embed declarative automated fuzzing and prompt regression scanners directly into containerized CI/CD pipelines as mandatory release quality gates.- Inject semantic faults and behavioral noise to evaluate multi-agent swarm resilience and configure robust infrastructure circuit breakers.- Decouple tool execution privileges from volatile model logic using relationship-based access control models.- Harden human-in-the-loop approval interfaces against context-spoofing and parameter manipulation exploits.- Establish weighted risk quantification frameworks that translate probabilistic alignment flaws into deterministic business risk metrics.Do not wait for a critical semantic breach to expose your core infrastructure. Secure your autonomous workflows, harden your multi-agent networks, and enforce strict policy-as-code gates today.Buy your copy now to deploy production-grade defense validation across your enterprise platform.…
Seller Inventory # 9798199961622
- Title
- Advanced Threat Modeling and Red Teaming for Agentic AI Systems : Identify, Simulate, and Defend Against Real-World Attacks on AI Agents, Multi-Agent Systems, and Enterprise AI Platforms
- Author
- Gibbs Marcel
- Publisher
- Independently Published Jun 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 13
- 9798199961622
- Item weight
- 566 grams
- Dimensions
- 254x178x17 mm
Advanced Threat Modeling and Red Teaming for Agentic AI Systems provides the definitive, production-first blueprint to secure non-deterministic software deployments. This comprehensive technical guide skips basic introductory concepts to deliver hard-hitting offensive engineering strategies, automated vulnerability testing pipelines, and zero-trust defensive hardening patterns. It addresses the unique architectural realities of modern multi-agent systems, shifting your security posture from reactive prompt filtering to code-enforced, continuous validation across your entire cluster fabric.
What advantages will you gain by engineering your security framework from the ground up? This manual equips platform architects, security engineers, and DevSecOps teams with the exact technical skills required to build an automated, self-healing defensive lifecycle.
By implementing the production-grade methodologies detailed inside, you will acquire the skills to:
- Build stateful autonomous red team agents to programmatically simulate complex, multi-turn adversarial cascades.
- Embed declarative automated fuzzing and prompt regression scanners directly into containerized CI/CD pipelines as mandatory release quality gates.
- Inject semantic faults and behavioral noise to evaluate multi-agent swarm resilience and configure robust infrastructure circuit breakers.
- Decouple tool execution privileges from volatile model logic using relationship-based access control models.
- Harden human-in-the-loop approval interfaces against context-spoofing and parameter manipulation exploits.
- Establish weighted risk quantification frameworks that translate probabilistic alignment flaws into deterministic business risk metrics.
Buy your copy now to deploy production-grade defense validation across your enterprise platform.
"Synopsis" may belong to another edition of this title.
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