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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsGive every AI agent a distinct, machine-verifiable identity; never make it operate as an undifferentiated copy of a person. Bind that identity to narrowly delegated permissions, short-lived credentials, an accountable user or service, and tamper-resistant records of actions and approvals. This approach limits damage from mistakes or prompt injection and gives security, IAM, platform, and compliance teams evidence of who—or what—did what.
What “agent identity” means
An AI agent is software that can plan or execute actions through applications, APIs, data stores, browsers, or other tools. Agent identity is the set of identifiers, authenticators, attributes, and permissions that represent that software to those systems.
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The agent should be distinguishable from both the human who requested work and the service or workload that hosts it. NIST describes this as treating agents as “first-class entities with their own unique identifiers, credentials, and associated entitlements that are bound to and by the identity of the user or system operating the agent.”
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- Which agent acted? Record a stable agent identifier, version or deployment identity, and the execution instance when relevant.
- Who or what authorized it? Record the human user, service, workflow, or policy that delegated the work.
- What was it allowed to do? Record the resources, operations, conditions, and duration of the authorization.
Keeping these identities separate prevents an agent’s activity from being misattributed to a person and allows an organization to revoke or constrain one agent without disabling an employee’s entire account.
Why an agent should not use a person’s login
Passing a user’s password, session cookie, personal access token, or broad API key to an agent is an accountability and security failure. If the agent sends an email, changes a record, or downloads data, the target system may see only the person’s identity. Investigators cannot reliably tell whether the person acted directly, an agent acted with permission, or a stolen secret was replayed.
NIST warns that credential sharing can create accountability, privacy, security, and legal problems. Static API keys and bearer tokens add a second weakness: anyone who obtains the value can often replay it until it expires or is revoked. Secrets can leak through source code, environment dumps, ticket attachments, markdown instructions, crash reports, telemetry, or ordinary application logs.
Use a delegation flow instead. The person or calling system authenticates normally; an authorization service issues the agent a credential representing a specific delegation; the resource server validates the agent and the delegated rights. The user remains accountable for approving the task, while the logs show that an agent performed the operation.
The identity model: user, agent, and workload
Document these principals before selecting protocols. They are related, but they are not interchangeable.
| Principal | Purpose | Typical evidence |
|---|---|---|
| Human user | Requests work, approves sensitive actions, or owns the business decision | Federated account, authenticator, session, approval event |
| AI agent | Plans and performs bounded tasks | Unique agent ID, credential, software version, execution ID |
| Workload or service | Hosts the agent or calls a downstream service | Service identity, namespace, deployment and attestation attributes |
| Resource server | Enforces access to an API, application, database, or tool | Policy decision, token validation, resource and action record |
An agent may run inside a service workload, but that does not mean the workload identity alone is sufficient. If several agents share one service credential, the resource server cannot distinguish them. Conversely, an agent identity does not replace the workload’s controls for network access, deployment integrity, or runtime isolation.
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How to give an AI agent its own identity
1. Inventory the agent and its execution paths
List every agent, orchestrator, tool connector, model endpoint, data source, and destination it can reach. Record whether the agent is persistent, short-lived, user-launched, scheduled, or triggered by another service. Include development and test deployments; forgotten nonproduction credentials frequently become production attack paths.
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2. Assign a stable identifier
Create an identifier that is unique within the trust domain and remains associated with the agent definition. Keep deployment or execution identifiers separate so you can correlate a single run without losing the long-term identity. Include ownership, purpose, environment, data classification, and approved tools as managed metadata.
3. Authenticate the agent cryptographically
Use credentials issued to the agent or its workload, rather than a human secret. Depending on the architecture, this can be a signed JSON Web Token (JWT), an X.509 certificate, or another credential supported by the resource server. Protect private keys in an appropriate secrets or key-management system, restrict which process can use them, and monitor issuance and use.
4. Record the delegating principal
Every authorization request should carry the identity of the user or system that initiated or approved the task. A delegation record should include the agent identifier, delegator, intended audience, allowed resources and actions, purpose or task identifier, start and expiry times, and any approval reference. Do not infer delegation merely because a request arrived from a trusted network.
5. Grant the minimum useful authority
Translate the task into specific operations: read a named dataset, create a draft, call one API method, or update records matching a defined condition. Avoid unrestricted administrator roles and avoid a single token that covers an entire application estate. Add context such as tenant, environment, device, network, risk score, time window, and data sensitivity when your policy engine supports it.
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Re-evaluate access when the task, tool, data classification, or risk changes. A research agent may read public material but require a new decision before accessing customer records. A deployment agent may prepare a change but require approval before production execution. Policy-based access control is one of the areas identified for the NCCoE agent-identity project.
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Credential design and lifecycle
NIST recommends dynamic, tightly scoped, audience-restricted credentials and notes that their lifetime should reflect an agent’s ephemerality. A credential created for a single task should not remain valid for months. Set the shortest lifetime that permits reliable completion, and provide explicit revocation for emergency response, user withdrawal, agent compromise, and deployment retirement.
| Lifecycle stage | Controls to implement |
|---|---|
| Issue | Authenticate the workload or agent, verify policy, bind the credential to an audience and delegation, and record issuance. |
| Use | Send only to the intended resource server; enforce scopes, claims, rate limits, and transaction limits. |
| Rotate | Renew automatically before expiry without exposing old and new secrets to logs or operators. |
| Revoke | Invalidate on compromise, policy change, user cancellation, agent retirement, or abnormal behavior. |
| Retire | Disable issuance, remove trust relationships, destroy keys according to policy, and preserve required audit evidence. |
Never place credentials in clear-text configuration, prompt templates, markdown instructions, source repositories, issue trackers, or routine logs. Redact authorization headers and token claims that contain sensitive values. DPoP, a proof-of-possession approach, can reduce some replay and token-theft scenarios by requiring a request to demonstrate control of a key; it does not replace secure key storage, authorization, monitoring, or revocation.
Technology choices to evaluate
No single mechanism is a universal compliance solution. Evaluate each option against your identity provider, resource servers, execution environment, and operational maturity.
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| Mechanism | Useful role | Questions to ask |
|---|---|---|
| OAuth 2.0 | Delegated authorization between a user, agent, client, and resource server | Can scopes, audiences, consent, expiry, and revocation express the task precisely? |
| SPIFFE | Workload identity for services across platforms and environments | Can each agent or workload receive a distinct identity, and can resource servers validate it? |
| JWT | Portable signed claims for identity, delegation, audience, and expiry | Are signing keys protected, claims minimized, and token replay addressed? |
| X.509 | Certificate-based authentication and mutual TLS | Who issues, rotates, validates, and revokes certificates at your scale? |
| DPoP | Sender-constraining tokens to a key under the caller’s control | Can clients securely protect keys and can all relevant resource servers validate proofs? |
| WIMSE | Emerging work for workload identity and secure service communication | Is the specification and implementation mature enough for your interoperability needs? |
| Identity Assertion JWT Authorization Grant | Emerging approach for exchanging an identity assertion for delegated access | Do your authorization server and resource servers support the required profiles? |
NIST identifies OAuth 2.0 and SPIFFE as enterprise foundations, JWT and X.509 as credential formats, and DPoP as a sender-constraining approach. It describes WIMSE and the Identity Assertion JWT Authorization Grant as emerging capabilities, so verify current specifications and implementation support before committing to them.
Approvals, high-impact actions, and delegation
Least privilege does not mean every action should be automatic. Define an approval policy for irreversible, external-facing, financially significant, privacy-sensitive, or production-changing operations.
- Let the agent prepare a draft, query, or change plan without execution authority.
- Present the exact operation, target, affected records, and predicted side effects to the approver.
- Bind the approval to the specific agent, task, resource, and expiry window.
- Require a fresh approval when the plan materially changes or risk increases.
- Record approval, denial, timeout, and execution outcomes as separate events.
Delegation should be explicit even when a machine starts the task. A scheduled workflow, ticketing system, or business process can be the authorizing system; record its identity and the human or policy that established its authority.
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What an agent audit trail should contain
Design logs so an investigator can reconstruct intent, authorization, execution, and result without relying on the agent’s own narrative. At minimum, capture:
- Agent identifier, execution identifier, software or policy version, and hosting workload.
- Delegating user or system, authentication context, tenant, and task or case identifier.
- Resource, operation, parameters or a protected hash of sensitive parameters, and intended audience.
- Authorization policy version, decision, scopes, conditions, and credential issuance and expiry.
- Human approval requirement and approval event, including who approved, what was shown, and when.
- Execution result, downstream response, error, retry, cancellation, and rollback information.
- Integrity protections, clock source, retention classification, and access history for the log itself.
The NCCoE concept paper raises tamper-evident action and intent logs and non-repudiation as design questions. It does not define a universal event schema, retention period, or legal sufficiency test. Select those controls with your incident-response, privacy, records-management, and legal teams.
Prompt injection: what identity controls can and cannot do
Prompt injection can cause an agent to treat untrusted text as instructions. Identity controls do not prove that an agent will resist such manipulation, and they do not eliminate the need for input isolation, tool validation, content handling, and model-specific defenses.
They can reduce the blast radius. If the agent has no delete permission, no unrestricted network path, a narrow audience, and a short-lived token, a malicious instruction has fewer options. Require a separate authorization decision for sensitive tools, validate parameters at the tool boundary, and treat retrieved documents and web content as data rather than authority. The NCCoE project explicitly considers prompt-injection prevention and impact reduction, but its concept paper is not a finalized control standard.
Human identity guidance versus agent identity guidance
NIST SP 800-63-4, published in July 2025, is the current revision of the Digital Identity Guidelines. It covers identity proofing, enrollment, authenticators, authentication, and federation for people interacting with government information systems over networks, and it supersedes SP 800-63-3. It can inform the human side of an agent workflow—such as how an operator authenticates and approves a transaction—but it is not a complete AI-agent identity standard.
The NCCoE concept paper published February 5, 2026 proposes work applying identity standards and practices to software and AI agents. Its project resource hub says the intended output includes an SP 1800-series practice guide with example architectures, implementations, build details, and laboratory lessons. The hub reported more than 600 responses to the concept paper. Those are project milestones, not evidence that a final guide or universal mandate already exists.
NIST’s August 27, 2026 article and its May 18, 2026 summary of responses to an AI-agent-security request for information describe active development and the need to adapt established cybersecurity principles. They do not establish a single architecture, a quantified incident rate, or a binding law. Organizations must map controls to their own jurisdiction, sector, contracts, and risk obligations.
A practical rollout checklist
- List every production and nonproduction agent, owner, workload, tool, data source, and destination.
- Assign unique agent and execution identifiers and publish ownership and purpose metadata.
- Choose an authentication method that resource servers can validate and operate at your scale.
- Implement explicit delegation linking the agent to a user or authorizing system.
- Define resource-, action-, audience-, context-, and time-limited permissions.
- Issue dynamic credentials; protect keys; redact secrets; rotate and revoke automatically.
- Separate preparation from execution and require human approval for defined high-impact actions.
- Log identity, delegation, policy, approval, action, result, and integrity evidence.
- Test stolen-token replay, revoked credentials, expired approvals, tool misuse, prompt injection, and rollback.
- Review project and standards status before claiming alignment or compliance.
Bottom line
An AI agent should be a separately identifiable workload with its own credentials and entitlements, while every action remains tied to the user or system that delegated it. Use narrow, audience-bound, preferably short-lived authorization; protect and rotate credentials; gate high-impact operations; and preserve tamper-evident evidence. NIST’s current material supports these principles and names useful technologies, but the NCCoE agent-identity work remains in development and is not a final compliance mandate.
Frequently Asked Questions
Should each run of an agent have a different identity?
Keep a stable identity for the agent definition, then add a unique execution or task identifier for each run. This preserves lifecycle management while allowing precise incident investigation and revocation.
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Is a service account acceptable for an AI agent?
Only when it is a distinct workload identity with narrowly defined permissions and an auditable delegation link. A shared account used by multiple agents or people destroys attribution.
How long should an agent token last?
Use the shortest lifetime that safely supports the task. A one-time or short workflow should not receive a credential that remains valid for months; exact durations depend on operational reliability and risk.
Do logs need to store the full prompt?
Not necessarily. Store enough protected context, hashes, task identifiers, policy decisions, and tool parameters to reconstruct authorization and action. Full prompts may contain personal or confidential data, so apply privacy and retention controls.
Can OAuth alone make an agent compliant?
No. OAuth can provide delegated authorization, but compliance also depends on identity separation, policy, credential protection, approvals, logging, revocation, and obligations specific to your organization.
What should happen when a user withdraws approval?
Stop issuing or accepting credentials derived from that delegation, cancel queued work, revoke active tokens where possible, and record the withdrawal and any actions completed before it took effect.
Is there already a final NIST standard specifically for AI-agent identity?
No final agent-specific compliance standard is established by the cited material. SP 800-63-4 addresses human digital identity, while the NCCoE project is developing practical agent and software identity guidance.
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