Is a local AI model server on the office network a security risk?
It can be, mostly through ordinary misconfiguration rather than anything exotic. Keeping data on your own hardware avoids sending it to an outside provider, which is a real advantage. The risks are the usual ones for a new server nobody planned: the API or web interface often listens on all interfaces without authentication, so anyone on the network can use the model, read conversation history or upload files; the server runs unpatched software that changes quickly; model files downloaded from public hubs can contain malicious code if they use unsafe formats; and documents fed into it for retrieval may be readable by everyone who can reach it. Treat it like any internal service: a named owner, authentication, binding to localhost or a restricted segment, updates, safe model formats from trusted sources, and a decision on which data may go in. From the Pro plan, NetSenX shows which hosts run or call local language-model runtimes and how much data moves, and its core detections flag scanning or lateral movement from that host on every plan.
This answer also appears, with more context, here: AI use and AI security