Intent capture is the process of recording why an action was authorized, not just that access was granted. For agentic AI, it binds the request, policy decision, and resulting action together so investigators can determine whether the system stayed within mandate.
Expanded Definition
Intent capture records the reason an action was authorized, not merely the fact that access was granted. In agentic AI and NHI operations, that means preserving the request context, the policy or guardrail evaluated, the decision outcome, and the resulting tool use or transaction so auditors can reconstruct NIST Cybersecurity Framework 2.0 style governance evidence.
This concept sits between authentication, authorization, and audit logging. Authentication proves who or what asked. Authorization proves whether the action was allowed. Intent capture proves why the system believed the action matched its mandate. That distinction matters because agentic systems may chain multiple tools, make delegated decisions, or execute on partial prompts, and the original purpose can be lost unless it is explicitly bound to the action record. Definitions vary across vendors on how much context must be retained, but no single standard governs this yet. NHI Management Group treats intent capture as a control evidence layer, not just a logging enhancement, because it supports later reconstruction of policy compliance, exception handling, and delegated authority.
The most common misapplication is treating generic access logs as intent capture, which occurs when teams record only timestamps and action names without the authorizing policy context.
Examples and Use Cases
Implementing intent capture rigorously often introduces storage, privacy, and telemetry overhead, requiring organisations to weigh forensic clarity against the cost of retaining richer decision records.
- An AI agent submits a cloud change request, and the system stores the user prompt, policy check, approved scope, and the deployment action together.
- A service account rotates a secret only after a policy engine records the maintenance window and ticket reference that justified the operation.
- A privileged workflow opens a production incident bridge, and the record links the alert source, the escalation policy, and the tool actions taken by the agent.
- A procurement assistant agent queries vendor pricing, and the audit trail preserves the data-access purpose so investigators can distinguish legitimate evaluation from data exfiltration.
- After a compromise, investigators correlate the action trail with the Salt Typhoon US telecoms breach to see whether stolen credentials were used within or outside their approved intent.
For implementation patterns, teams often borrow from structured logging and authorization evidence practices described by NIST Cybersecurity Framework 2.0, but the agentic context usually demands tighter binding between policy decision and execution than conventional logs provide.
Why It Matters in NHI Security
Intent capture is essential when NHIs, API keys, and autonomous agents can act faster than human reviewers can intervene. Without it, an organisation may know that a token was used, but not whether the use reflected an approved mandate, a prompt injection outcome, or a lateral movement attempt. That gap weakens incident response, change control, and post-breach attribution. It is especially important where excessive privilege or secret exposure creates ambiguous action trails, which is common in NHI-heavy environments. NHI Management Group reports that 80% of identity breaches involved compromised non-human identities such as service accounts and API keys, making action provenance critical to determining what the attacker was actually able to do. The same governance pressure appears in major compromise reporting such as the Microsoft Midnight Blizzard breach, where identity abuse and access path analysis are inseparable from response.
Organisations typically encounter the need for intent capture only after a suspicious action must be defended, at which point missing provenance makes containment and accountability 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 Agentic AI Top 10 and OWASP Non-Human Identity Top 10 address the attack and risk surface, while NIST CSF 2.0 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Agentic AI Top 10 | AC-01 | Agentic systems need traceable decision-to-action provenance for authorized tool use. |
| OWASP Non-Human Identity Top 10 | NHI-07 | NHI auditability depends on linking credentials, decisions, and resulting actions. |
| NIST CSF 2.0 | DE.AE-3 | Anomalous behavior detection improves when actions are tied to stated intent. |
Log intent context so responders can validate whether activity matched expected use.
Related resources from NHI Mgmt Group
- What is the difference between logging actions and logging intent for AI agents?
- What is the difference between role-based access and intent-based access for agents?
- What is the difference between RBAC and intent-aware access for autonomous workflows?
- What is the difference between access control and intent governance for AI agents?
