A borrowed user session makes the agent look like the human, which blurs accountability and complicates revocation when the session ends. An agent acting under its own identity keeps the acting subject separate from the delegating authority, so downstream systems can verify who did the work and on whose authority. That separation is the basis for clean audit trails and constrained delegation.
Why borrowed sessions blur accountability while own identity preserves delegation
Borrowed user sessions collapse two different roles into one runtime identity: the human who granted access and the agent that executed the work. That makes attribution fragile, especially when the session expires, is revoked, or is reused for multiple actions. An agent with its own identity keeps those roles distinct, so the delegating authority and the acting subject can be evaluated separately.
That separation also changes how systems make trust decisions. With a borrowed session, downstream services usually see only the human session context, which can hide whether the action was initiated by a person or by automation. With a first-class agent identity, policy can be tied to the agent's permissions, purpose, and lifecycle rather than to whatever access the user happened to have at the time.
For broader background on agent identity models, NHIMG's Agentic AI Identity Guide explains how delegated authority, authentication, and retirement fit together.
What changes for audit trails, revocation, and least privilege
Audit trails are much cleaner when the actor is explicit. A borrowed session can make logs look like the human performed every action directly, which complicates incident review, approval tracing, and non-repudiation. An agent identity lets you record who sponsored the action, which identity actually executed it, and which policy allowed it.
Revocation behaves differently too. If the agent depends on a borrowed session, access can vanish abruptly when the user signs out, resets a password, or loses access for unrelated reasons. If the agent has its own identity, you can revoke or narrow the agent's authority without disrupting the user's own access. That is the practical difference between delegated access and identity confusion.
Least privilege is easier to enforce with a dedicated agent identity because the agent can receive only the exact scopes, resources, and duration it needs. Borrowed sessions tend to inherit whatever the human already has, which is often broader than the task requires. NHIMG's AI Agent Authorisation Guide covers task-scoped access and per-action policy decisions, while Human vs Non-Human Identity explains why shared access patterns create governance ambiguity.
Why this distinction matters in real agent designs
The choice affects how safely an organisation can operate agents at scale. Borrowed sessions are tempting because they are quick to implement, but they often create hidden coupling between user availability and agent availability. They also make it harder to distinguish legitimate delegation from credential abuse, especially when the same session can be used interactively and programmatically.
An own-identity model is more robust when the agent needs to operate over time, across systems, or under reviewable policy. It supports clearer ownership, rotation, retirement, and access review. It also makes it easier to enforce boundaries such as human approval for sensitive actions, because the agent can be evaluated as its own actor instead of as an extension of the user session.
For control selection and implementation trade-offs, Agent Identity and Access Guide is the most direct starting point, and Identity Governance for AI Agents Guide is useful when the question shifts from runtime access to lifecycle governance.
Risk and Threat Considerations
Borrowed sessions increase the chance that a compromise, mistake, or overly broad grant will be attributed to the wrong actor. They also make session theft, replay, and privilege carry-over more damaging because the agent is effectively operating with human-equivalent authority. The main operational risk is not just abuse, it is ambiguity: when something goes wrong, teams may not be able to tell whether the user, the agent, or both are responsible.
Failure mechanism: The agent inherits a live human session, so downstream systems cannot distinguish delegated automation from direct human use. When that session is reused, expires, or is revoked, audit, containment, and policy enforcement become inconsistent.
Impact: Organisations lose clean attribution, struggle to revoke only the agent's authority, and may overestimate how much control they still have over the action path. That widens the blast radius of both normal operational errors and malicious reuse of the same session context.
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 addresses the attack and risk surface, while NIST SP 800-53 Rev 5 and NIST SP 800-57 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST SP 800-53 Rev 5 | IA-5 — Authenticator Management | Covers lifecycle control of credentials used by users and agents. |
| IA-2 — Identification and Authentication (Organizational Users) | Applies because borrowed sessions collapse human and agent authentication context. | |
| AC-6 — Least Privilege | Directly supports scoping an agent's authority separately from the user's broader access. | |
| Recommendation — Restrict, rotate, and revoke the credentials that underpin delegated agent access. Require distinct authentication context for the human sponsor and the acting agent. Limit agent permissions to the minimum authority needed for each task. | ||
| OWASP Agentic AI Top 10 | ASI03 — Identity & Privilege Abuse | The question is about whether an agent acts under borrowed or owned identity. |
| ASI09 — Human-Agent Trust Exploitation | Borrowed sessions can blur whether a human or agent initiated the action. | |
| Recommendation — Bind each agent action to its own identity and delegated privilege boundary. Make delegation explicit so users and systems can verify who acted and why. | ||
| NIST SP 800-57 | Key Management | The identity split can depend on how delegated credentials and tokens are issued and retired. |
| Recommendation — Govern delegated tokens and keys so agent authority can be revoked independently. | ||
Practitioner Guidance
What to verify: Check whether the agent has a unique principal, unique credentials, and a revocable lifecycle of its own. If the answer is "it uses the user's session," treat that as a temporary integration pattern, not a stable operating model.
Decision rule: Use a borrowed session only for short-lived, low-risk interactions where the user's authority and the agent's action should be identical. Use a distinct agent identity whenever you need durable auditability, scoped delegation, or independent revocation.
Practitioner takeaway: The key design choice is whether you want the agent to borrow authority or own a bounded identity; if you cannot separate those two in logs and revocation, you do not yet have a reliable delegation model.
Related resources from NHI Mgmt Group
- What is the difference between human identity governance and AI agent governance?
- Why is identity such a critical factor in securing AI agent systems?
- How do organisations decide whether an agent session is acting as a user or as an app?
- What breaks when an AI agent can browse and act under a user’s identity?
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Reviewed and updated by the NHIMG editorial team on November 5, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org