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Whitepaper

AI Data Center & AI Factory Security Blueprint

As enterprises build out dedicated AI infrastructure including GPU clusters, model training pipelines, and inference endpoints, they introduce attack surfaces that traditional security tools were never designed to protect. This blueprint addresses the full security lifecycle of an AI data center, from physical isolation and network segmentation to runtime protection of containerized workloads and prevention of model weight exfiltration. Security architects and infrastructure teams will find prescriptive guidance on threat modeling AI factory environments, applying zero-trust principles to model serving layers, and preparing for emerging regulatory requirements around AI system integrity. Organizations building or scaling AI infrastructure will come away with a concrete security architecture that protects both the models and the data that power their AI initiatives.