Governance should sit with the security and platform teams, but it must be designed around developer usability. Security owns policy, auditability, and revocation rules, while engineering needs low-friction access patterns that do not force manual key handling. Shared governance works best when controls are centralized, identity-aware, and visible to both groups in real time.
How Governance Should Be Split When Security and Engineering Both Depend on Model Access
Model access governance works best when security defines the policy boundary and engineering defines the usability boundary. Security should own approval logic, audit requirements, revocation criteria, and exceptions, because those decisions determine who can reach models, under what conditions, and how quickly access can be withdrawn. Engineering should own the access experience, integration patterns, and developer workflows so that governance does not collapse into manual key sharing or ad hoc bypasses.
The practical issue is that model access is not just a permission problem. It also shapes how teams build, test, deploy, and monitor systems that call models through APIs, gateways, or internal services. If ownership is vague, teams often compensate with shared secrets, duplicate credentials, or informal approvals, which makes revocation and traceability weaker. NHI Management Group treats this as an identity and operating model question as much as a control question, because the governance design must fit the way access is actually consumed. For broader governance context, the NIST Cybersecurity Framework 2.0 is useful when teams need a cross-functional structure for accountability and control visibility.
In practice, many security teams discover ownership gaps only after developers have already built around a workaround, rather than through intentional access design.
What Shared Ownership Needs to Work Day to Day
Shared governance only works when the ownership model is explicit about decision rights. Security should define who may request access, which model classes are approved, what logging is mandatory, and which events trigger suspension or review. Engineering should define how access is requested, how identities are bound to workloads or users, and how access is delivered without exposing reusable secrets. That split keeps policy centralised while still allowing teams to move quickly.
In operational terms, the strongest pattern is a single governance process with two responsibilities: security approves the rules and reviews exceptions, while engineering operationalises those rules in the delivery path. Access should be tied to named identities, service accounts, or workload identities rather than to shared project tokens that are passed around informally. Where access is mediated through an internal platform, the platform team usually becomes the control plane owner, but not the policy owner. That distinction matters because the group that runs the tooling is not always the group that should decide access eligibility.
- Security owns policy, risk acceptance, logging requirements, and revocation thresholds.
- Engineering owns workflow design, automation, and integration with developer tooling.
- Platform or IAM teams implement the technical control plane and enforce the decision.
- Both teams should see request, approval, and usage telemetry in near real time.
This is also where machine identity discipline matters. If model access is granted through API keys, service credentials, or other non-human identities, governance should cover ownership, rotation, and offboarding explicitly. The OWASP Non-Human Identity Top 10 is a strong reference when the question is really about controlling access paths used by workloads and automation. This guidance breaks down when organisations treat the approval workflow as a one-time ticket instead of an ongoing control over live identities and credentials.
Where Shared Governance Breaks, and What Teams Should Standardise
Tighter governance often increases coordination overhead, requiring organisations to balance fast access against stronger accountability. The trade-off is most visible when engineering wants self-service and security wants formal review. If the process is too rigid, teams route around it. If it is too loose, nobody can explain who authorised access or how to revoke it safely.
The main edge case is delegated ownership. In some organisations, the security team cannot practically approve every model request, so authority is delegated to platform leads under security policy. That can work, but only if the delegation is bounded by clear criteria, documented exceptions, and periodic review. Another common variation is environment-based access, where development, staging, and production have different rules. That is sensible, but only if the policy makes those differences explicit rather than assuming the same identity or key can move everywhere.
Teams should also separate human developer access from machine-to-machine access. The governance controls may look similar, but the failure modes are different. Human access depends on user lifecycle, while model-calling services depend on secret handling, workload identity, and service ownership. Many organisations underestimate how quickly access governance becomes fragile once multiple teams and automation layers start sharing the same path to the model. Standardisation should therefore focus on a single request path, a single approval record, and a single revocation mechanism that both teams can trust.
Risk and Threat Considerations
When model access is jointly depended on by security and engineering, the material risk is governance drift: access becomes easy to grant but hard to explain, audit, or revoke. That creates exposure both through over-permissioned identities and through hidden workarounds such as shared keys, copied tokens, or informal exceptions.
Failure mechanism: If ownership is unclear, engineering optimises for delivery speed and security optimises for control, which often produces parallel access paths, duplicated credentials, and incomplete logging. That weakens accountability and increases the chance that access persists after a team, workload, or project no longer needs it.
Impact: The organisation can lose traceability over who used which model access path, struggle to revoke compromised credentials quickly, and inherit a control environment where policy exists on paper but not in the actual workflow.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 address the attack and risk surface, while NIST CSF 2.0 and CIS Controls v8 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST CSF 2.0 | GV.RM-01 — Risk Management Strategy | Model access governance is a cross-functional security governance issue. |
| Recommendation — Assign clear accountability for model access policy, exceptions, and review cadence. | ||
| CIS Controls v8 | 5.1 — Establish and Maintain an Inventory of Assets | Access ownership depends on knowing which identities and paths exist. |
| 6.3 — Manage External Access | Shared model access often involves third-party or cross-team access paths. | |
| Recommendation — Inventory every model access path and tie it to a responsible owner. Restrict and review non-standard access paths to the model. | ||
| OWASP Non-Human Identity Top 10 | NHI-01 — Inventory and Ownership | Model access via service identities needs clear ownership and lifecycle control. |
| NHI-03 — Secrets and Credential Management | Governance fails when teams rely on shared keys or unmanaged tokens. | |
| NHI-05 — Lifecycle and Revocation | The question hinges on who can remove model access when needed. | |
| Recommendation — Assign each model credential or workload identity to a named owner. Centralise credential handling and eliminate ad hoc shared secrets. Define revocation rules that security can execute without delay. | ||
Practitioner Guidance
What to prioritise: Define one owning function for policy and exception approval, then document the engineering team’s role in making access usable without shared secrets or manual handling. If both teams are “owners” in the same way, accountability usually weakens.
What to verify: Check whether every access path maps back to a named human or workload identity, a current owner, and a revocation method that can be executed without cross-team ambiguity. If any of those cannot be shown quickly, the governance model is not mature enough to trust.
Practitioner takeaway: The right ownership model is not a compromise between security and engineering; it is a clean split between policy authority and delivery responsibility, with identity and revocation treated as first-class operating requirements.
Related resources from NHI Mgmt Group
- How should security teams run access reviews for non-human identities?
- How should security teams govern non-human identities that have persistent access?
- What is the difference between role-based access and API key governance for NHI security?
- How should security teams use IAST and RASP in NHI governance?
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on September 7, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
