A private AI deployment can give an organisation more control over infrastructure and network policy. It does not automatically make the application secure or prove that no information leaves the environment.
Start with a threat model and the actual data path. The model runtime, retrieval store, tools, logs, updates and operational access all belong in the review.
Define what private means
On-premise, private cloud, a private endpoint and an air-gapped environment are different arrangements. A server can be locally hosted and still reach external services. A private network can still have configured outbound routes and provider administration.
Document where information is processed and stored, who can access it and which external dependencies remain. Include backups, support access, telemetry and model or package downloads.
Use contractual and technical evidence to assess the arrangement. A label such as “sovereign” should not replace a description of jurisdiction, access and operating responsibility.
Protect the software and model supply chain
Track the model, runtime, dependencies and configuration versions deployed. Obtain artifacts through approved sources and verify integrity where the publisher provides a supported mechanism.
A valid signature or hash establishes a relationship to a particular artifact. It does not prove that the model is free of harmful behaviour, backdoors or task-specific weaknesses. Evaluate behaviour separately.
Review model licences and permitted uses. Open weights do not necessarily mean unrestricted use, ownership of the original model or freedom from all external dependencies.
Restrict access to data and tools
Use identities and permissions appropriate to the task. Keep service credentials outside prompts. Separate the ability to read a record from the ability to change it.
For retrieval, apply access controls before restricted passages reach the model. Protect caches and derived indexes too. Revoked access should not leave a stale copy available through another route.
Limit the operations exposed to an agent. Validate parameters and enforce authorisation in software before executing a model-proposed request. Private inference does not prevent an excessive tool permission from causing damage.
Treat documents as untrusted input
A retrieved page can contain text intended to redirect the model or extract information. Locally hosting the model does not remove this prompt-injection problem.
Use layered controls: narrow tools, clear data boundaries, input/output handling and review of high-impact actions. Test adversarial examples relevant to the application. No prompt or filter should be presented as a complete solution to every injection attempt.
OWASP’s prompt-injection guidance describes the risk and why retrieval or tuning alone is insufficient protection.
Keep operational evidence proportionate
Logs can help identify what the application received, requested and changed. They can also become another store of sensitive information.
Choose the events and references needed for investigation. Restrict access, redact unnecessary content and define retention. A model’s generated reasoning is not a complete account of its internal computation.
Test recovery and incident handling. Know how to revoke a connection, stop new tasks and identify work that may have been affected. Stopping a process does not reverse an external action already completed.
Separate compliance from deployment location
Privacy and sector obligations depend on the processing and organisational role. HHS cloud guidance, for example, permits relevant cloud processing under appropriate agreements and safeguards rather than imposing a universal on-premise mandate.
A private deployment may satisfy a project requirement, but it does not certify compliance. Legal advisers and accountable owners determine the applicable obligations; engineering implements and tests the agreed controls.
Our AI Security and Governance capability covers these practical boundaries around custom AI systems.
Written by Anshul Kaushik, Managing Director at Ryzolv.
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