The ability to trace an action back to the specific identity that initiated it, even when a proxy or server executes the request. This is essential in shared tool environments because it preserves accountability, supports investigation, and prevents shared credentials from hiding the true actor.
Expanded Definition
Per-user attribution is the capability to preserve the originating user’s identity when an action is carried out by an intermediary, such as an AI agent, proxy, workflow runner, or application server. In NHI and IAM practice, it is what prevents a downstream execution layer from becoming an accountability black box.
In mature implementations, the execution service may authenticate itself as a workload, but the audit record still carries the user context, approval context, and request lineage. This differs from simple impersonation, where a system acts only as itself, and from shared service accounts, where multiple people blur into one operational identity. Standards guidance is still evolving across vendors, but the principle aligns closely with traceability and accountability expectations in NIST Cybersecurity Framework 2.0 and identity governance patterns used in NHI controls.
The most common misapplication is treating a logged service account as sufficient attribution, which occurs when the original caller is not preserved through proxy hops, delegated tool calls, or batched automation.
Examples and Use Cases
Implementing per-user attribution rigorously often introduces extra telemetry, token propagation, and correlation overhead, requiring organisations to weigh audit fidelity against added implementation complexity.
- An AI agent uses a ticketing API to create a change request, but the audit trail records the employee who approved the action rather than only the agent runtime identity.
- A shared automation runner executes a database query on behalf of an analyst, and the query log includes the analyst ID, workflow ID, and approval timestamp for later investigation.
- A developer triggers a deployment through an internal portal, and the downstream CI/CD system retains the developer’s identity through delegated credentials instead of collapsing all activity into one pipeline account.
- A proxy service forwards requests to a SaaS platform, and the platform logs the originating user context so incident responders can distinguish delegated use from direct workload access.
NHIMG research shows that only 5.7% of organisations have full visibility into their service accounts, which makes attribution gaps especially dangerous when shared execution layers are involved. That visibility problem is a recurring theme in the Ultimate Guide to NHIs, and it is one reason traceability must be engineered rather than assumed. For implementation patterns, teams often compare their logging design against the NIST Cybersecurity Framework 2.0 emphasis on detectability and auditability.
Why It Matters in NHI Security
Without per-user attribution, incident response loses the ability to answer a basic question: who actually caused the action. That breaks investigation, weakens non-repudiation, and makes shared credentials or agent-mediated workflows appear cleaner than they are. In NHI environments, this often leads to false confidence in access reviews because the platform shows what executed, not who initiated it.
The risk is amplified when agents, proxies, and orchestrators operate with elevated privileges. A single automated account can hide dozens of human triggers if user context is not propagated end to end. This is especially dangerous in regulated environments where approvals, segregation of duties, and forensic evidence all depend on a complete trail. NHIMG reports that 80% of identity breaches involved compromised non-human identities such as service accounts and API keys, and attribution gaps make those events much harder to contain and explain. The same Ultimate Guide to NHIs also notes that 97% of NHIs carry excessive privileges, which magnifies the impact of any missing provenance.
Organisations typically encounter the cost of weak attribution only after a suspicious action cannot be tied back to a person, at which point per-user attribution becomes operationally unavoidable to address.
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 and OWASP Agentic AI Top 10 address the attack and risk surface, while NIST CSF 2.0, NIST Zero Trust (SP 800-207) and NIST SP 800-63 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-08 | Traceability and audit logging for delegated NHI actions support accountable execution. |
| NIST CSF 2.0 | DE.CM-7 | Logging and monitoring controls depend on reliable origin attribution for events. |
| NIST Zero Trust (SP 800-207) | AC-6 | Least privilege and explicit context require knowing who initiated delegated access. |
| NIST SP 800-63 | IAL2 | Identity assurance supports confidence that the originating user was properly established. |
| OWASP Agentic AI Top 10 | A2 | Agentic systems need provenance controls to avoid opaque autonomous actions. |
Capture user provenance in logs so monitoring can distinguish operator intent from workload execution.
Related resources from NHI Mgmt Group
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Reviewed and updated by the NHIMG editorial team on August 20, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
