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Chapter 1 · 2026

Cyber Warfare and AI Agents: Strengthening National Security Against Advanced Persistent Threats (APTs)

Rahul Vadisetty, Anand Polamarasetti, Vivek Varadarajan

Abstract

This study addresses the application of Artificial Intelligence (AI) agents to enhance national security against Advanced Persistent Threats (APTs) in cyber warfare. With the increasing sophistication of cyber threats, particularly APTs, AI has become a critical tool for detecting, mitigating, and preventing these targeted and persistent cyberattacks. The study examines the types of AI agents applied in cybersecurity, including signature-based, anomaly-based, and autonomous systems.

Eigenvector Insight — Zone III / PASF-PADE AnalysisNot part of the original paper
Eigenvector Research — Marco van Hurne
How this paper contributes to solving the Zone III problem (PASF-PADE)

This paper directly addresses one of the core structural challenges in Zone III deployments. The research on Cyber warfare, AI agents, national security provides evidence-based foundations that enterprise architects cannot ignore when designing long-horizon autonomous workflows. The findings challenge the assumption that a base language model — however capable — can handle the complexity of durable, governed, multi-step execution without explicit architectural intervention. For Zone III practitioners, this paper belongs in the required reading list.

Why AI is not sufficient for Zone III without this

Zone III refers to high-complexity, high-risk, long-running agentic workflows — the class of enterprise AI deployments where a single failure can cascade across hundreds of steps. Standard AI models, trained to predict the next token, are not inherently designed for durable, governed, multi-step execution. This paper addresses one or more of the structural gaps that make Zone III deployments unsafe without explicit architectural intervention.

Topics

Cyber warfareAI agentsnational securityAdvanced Persistent Threatscybersecurityautonomous systems