Should organisations treat model registries differently from other code platforms?

Why This Matters for Security Teams

Model registries are not just storage systems for files; they are trust anchors for downstream deployment pipelines, agents, and applications. If an attacker modifies a model artifact, metadata, or version pointer, the compromise can propagate far beyond the registry itself. That is why model registries need to be governed as a blend of identity, software supply chain, and release integrity. NIST’s NIST Cybersecurity Framework 2.0 is useful here, but it does not by itself capture the identity-specific risks of non-human actors.

NHIMG research shows how often secrets and non-human identities fail in practice: the Ultimate Guide to NHIs — The NHI Market notes that 80% of identity breaches involved compromised non-human identities such as service accounts and API keys. In a model registry, those identities often have publishing, approval, or promotion privileges, so a single leaked token can become a broad trust failure. In practice, many security teams encounter registry abuse only after a model has already been repackaged or promoted into a trusted environment.

How It Works in Practice

A useful operating model is to treat the registry as both a privileged identity system and a controlled software distribution point. That means the registry should not rely on shared admin accounts or long-lived static tokens. It should instead use workload identity for automation, short-lived credentials for publishing, and tightly scoped roles for human reviewers. Access to upload, approve, sign, and promote models should be separated, because the ability to change metadata can be just as dangerous as the ability to replace the artifact itself.

At minimum, security teams should align the registry with four control layers:

• Strong authentication for every human and machine publisher, with no shared credentials.
• Fine-grained authorisation for model upload, approval, rollback, and deletion.
• Artifact integrity controls such as signing, hash verification, and provenance tracking.
• Audit logging that captures who changed what, when, and through which automation path.

This is where NHI discipline becomes operationally important. The Schneider Electric credentials breach illustrates how exposed credentials can create a downstream trust problem, not just an access problem. The right pattern is to issue just-in-time access for registry automation, then revoke it after the task completes. Standards such as NIST Cybersecurity Framework 2.0 support the broader governance model, but the registry also needs explicit non-human identity lifecycle controls and supply-chain validation. These controls tend to break down when model promotion is automated across multiple environments because trust decisions get copied faster than review checkpoints.

Common Variations and Edge Cases

Tighter registry control often increases release friction, so organisations have to balance velocity against provenance and rollback safety. That tradeoff becomes more visible in environments where data science teams publish models directly, CI/CD systems auto-promote artifacts, or third-party partners need controlled access.

Best practice is evolving for model registries that serve both internal and external consumers. There is no universal standard for this yet, but current guidance suggests treating externally shared registries as higher risk than internal package stores because a model can be both a code artifact and an operational dependency. The access model should also differ from source code platforms: code review alone is not enough if the registry can alter runtime behaviour after approval.

NHIMG’s Ultimate Guide to NHIs highlights that 71% of NHIs are not rotated within recommended time frames, which matters here because long-lived registry tokens are difficult to contain once exposed. Shared training environments, notebook workflows, and federated teams are the main edge cases where this guidance weakens, because identity boundaries and promotion paths are often too fluid for static RBAC alone.

Related resources from NHI Mgmt Group

• When should organisations treat model enumeration as suspicious?
• Should organisations treat non-human identities differently from human users in governance?
• When should organisations sandbox code execution in agentic platforms?
• Should organisations treat certificates and tokens like other non-human identities?