A model hub is a central platform where teams publish, discover, version, and deploy machine-learning models, datasets, and related artifacts. In practice, it acts like a software supply-chain repository for AI. Because it sits between developers, data, and runtime systems, compromise of a hub can affect many downstream applications at once.
In cyber security, model hubs matter because attackers may upload poisoned datasets, backdoored models, or malicious dependencies, or steal access tokens to replace trusted artifacts. Defenders reduce risk with strong identity controls, signed commits and artifacts, malware scanning, provenance checks, and least-privilege access to publishing and deployment workflows. Audit logs and approval gates help detect tampering before a bad model reaches production.