Agentic Cybersecurity: Engineering Autonomous AI Defense

Agentic Cybersecurity: Engineering Autonomous AI Defense

Cybersecurity is moving beyond traditional automation toward intelligent systems capable of continuously analyzing telemetry, investigating threats, using security tools, and executing controlled defensive actions.

Agentic Cybersecurity: Engineering Autonomous AI Defense provides a practical technical overview of how to design, build, secure, and operate autonomous AI-driven cybersecurity systems.

The title covers the complete architecture of modern cyber agents, including perception, reasoning, memory, tool calling, planning, execution, and verification. It explores how AI agents can be integrated with SIEM, EDR, network monitoring, identity platforms, cloud infrastructure, vulnerability scanners, threat intelligence, and forensic tooling.

Across 48 chapters, you will explore:

* Autonomous SOC operations and alert triage

* AI-powered threat hunting and anomaly detection

* SIEM, EDR, network, and security API integration

* Agent memory and telemetry processing

* PCAP analysis and endpoint forensics

* Threat intelligence and MITRE ATT&CK mapping

* Cloud, Kubernetes, and attack-surface security

* Autonomous containment and incident response

* Identity revocation and network isolation

* Vulnerability analysis and exploitability verification

* Automated code and infrastructure remediation

* Multi-agent security architectures and autonomous red teaming

* Agent runtime security and prompt-injection defense

* Sandboxing, least privilege, and deterministic guardrails

* Cryptographic provenance and audit trails

* Human-in-the-loop security workflows

* Local and air-gapped LLM deployments

* LLMOps, observability, benchmarking, and evaluation

* Compliance-as-code and supply-chain security

* Edge and IoT defense

A central theme is controlled autonomy. Security agents must be powerful enough to investigate and respond, while remaining constrained by authorization policies, deterministic safeguards, isolation, verification, and human oversight.

The book treats agentic cybersecurity as a systems-engineering discipline rather than simply connecting an LLM to security tools. It examines the architecture required to turn AI reasoning into reliable, auditable, and operational defensive capabilities.

Who Is This For?

This title is aimed at cybersecurity professionals, security engineers, SOC analysts, threat hunters, incident responders, DevSecOps engineers, security architects, AI/ML engineers, security researchers, and technically experienced practitioners interested in autonomous cyber defense.

Whether you are designing an AI-powered SOC, experimenting with local security agents, or researching the future of autonomous defense, this title provides a comprehensive technical foundation for building the next generation of cybersecurity systems.