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Hands-On Agentic AI for DevSecOps: A Practical Guide to Building Autonomous Security Agents, Secure Tool Sandboxing, and Self-Correcting Software Pipe
Paperback
General ComputersProgrammingComputer Security
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Publisher: Independently Published
Pages: 174
Weight: 0.69
Height: 0.37 Width: 7.00 Depth: 10.00
Language: English
Traditional software security boundaries are broken, and automated scanners only shift the cognitive burden of remediation onto overwhelmed engineering teams. When a vulnerability flags in an active code branch, human intervention remains the ultimate bottleneck, slowing down deployment velocities and exposing infrastructure to windowed exploits.
Are your engineering teams losing the battle against security debt and alert fatigue? Do you want to move large language models out of passive text sandboxes and insert them directly into your development pipelines as programmatic self-healing infrastructure utilities?
This manual delivers the production-grade, asynchronous blueprint to transform security from a reactive human chore into an autonomous control plane. Moving completely away from raw generative AI capability alone, this guide wraps probabilistic models inside strict, deterministic engineering frameworks to engineer resilient, zero-trust architectures from scratch.
Unlike theoretical abstractions or cloud vendor marketing texts, this book stands out by delivering complete, self-contained Python and Model Context Protocol (MCP) implementations. Every chapter provides hands-on patterns for building asynchronous shell execution engines, kernel-level containerization rules, rule-based output validation, and adversarial multi-agent negotiation frameworks.
By implementing these patterns systematically, you will gain the precise architectural knowledge to:
Construct turn-based execution frameworks pitting Builder Agents against Adversarial Critic Agents.
Implement safe bidirectional file transfer protocols using memory-buffered TAR streams to isolate host filesystems.
Enforce semantic guardrails using real-time vector embedding input classifiers to block prompt injections.
Combine probabilistic models with deterministic abstract syntax tree (AST) parsers to eliminate regressions.
This practical masterclass is written directly for technical leaders, principal DevSecOps architects, application security engineers, and software systems designers driving enterprise infrastructure practices.
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