TL;DR: AI agent credentials are being issued, stored, rotated, and revoked faster than manual processes can reliably track them, leaving organisations with credentials nobody can name, locate, or retire, according to Unosecur. The governance assumption that access exists long enough for periodic review collapses when agent credentials are created, used, and discarded at machine speed.
At a glance
What this is: This is a practical analysis of AI agent credential lifecycle management, with the key finding that issuance, storage, rotation, and revocation must be treated as one continuous control chain.
Why it matters: It matters because IAM, PAM, and NHI programmes that rely on periodic human-paced review will miss short-lived and fast-spawning agent credentials unless lifecycle control is redesigned for runtime speed.
👉 Read Unosecur's analysis of AI agent credential lifecycle management
Context
AI agent credential lifecycle management is the discipline of issuing, storing, rotating, and revoking credentials for non-human identities that act on behalf of an autonomous or semi-autonomous workflow. The problem is not just volume, but speed: agents can create credentials faster than teams can inventory them, which exposes gaps in NHI governance and lifecycle control.
Most credential programmes were built around human employment cycles, not task-scoped agents that may exist for an hour or run continuously while their surrounding workflow changes. That mismatch is why quarterly access reviews, shared service accounts, and manual revocation checks break down when the subject is an AI agent rather than a person.
Key questions
Q: What breaks when AI agents are connected through personal accounts or shared credentials?
A: Shared or personal credentials break accountability, lifecycle control, and revocation. If an agent inherits a human account, security teams lose clean ownership and cannot reliably attest what the identity can do or when it should be disabled. That creates an unmanaged backdoor into systems that may persist after the original setup is forgotten.
Q: Why do long-lived credentials create a bigger risk for AI agents than for traditional automation?
A: AI agents can choose tools and sequence actions dynamically, so long-lived credentials become durable authority across many unpredictable requests. That makes it harder to prove least privilege, track accountability, or limit blast radius. Traditional automation is usually fixed and bounded, while an agent can reuse the same secret in ways the original design did not anticipate.
Q: What are the signs that AI agent credential governance is breaking down?
A: Common warning signs include credentials scattered across unrelated vault items, weak naming that makes agent access hard to search, and no clear separation between human and agent workflows. Another signal is difficulty reissuing updated credentials after rotation, which usually means the organisation cannot quickly see where the agent’s access is retained.
Q: Who should own governance for AI agent credential custody?
A: Ownership should sit with IAM, PAM, and platform security together, because the issue spans identity lifecycle, privileged credential handling, and workload execution. Teams should govern where the token lives, how it is bound to the process, and whether the runtime can replay it outside the intended request path.
Technical breakdown
Issuance and scope: why broad credentials become the default
Credential issuance is the first control point, and it is where scope drift begins. Under delivery pressure, teams often grant broad, long-lived access because defining the narrow scope an agent actually needs takes longer. For AI agents, that trade-off is especially risky because the credential is the identity boundary, not just a convenience token. If the credential is not tied to a specific agent identity, defined scope, and expiry, later rotation and revocation have to compensate for a mistake made at creation time.
Practical implication: set agent credentials to task-specific scope and expiry at issuance, not after deployment.
Storage and retrieval: why embedded secrets outlive the deployment
Credential storage failures are usually mundane, not exotic. Secrets end up hardcoded in repositories, pasted into configuration files, or embedded in workflow definitions because that path is fastest. For AI agents, those shortcuts create a durable exposure path because a credential inside code or an image survives rotation attempts in the issuing system. The storage boundary also extends to tool interfaces such as MCP connections, where the agent may need to retrieve secrets at runtime from a governed vault instead of carrying them in the artifact.
Practical implication: move agent credentials into a governed secrets store and remove embedded secrets from code, images, and workflow files.
Rotation and revocation: why the lifecycle must stay continuous
Rotation and revocation fail when they are treated as separate admin events instead of one lifecycle chain. Short-lived credentials reduce the need for manual rotation, but longer-lived agent credentials still need event-triggered change when behaviour, scope, or tooling changes. Revocation is weaker than many dashboards suggest because disabling the source credential does not always terminate downstream sessions or secondary tokens already minted from it. That means the real control is not just deactivation, but confirming that no residual access path remains open.
Practical implication: tie rotation and revocation to events, and verify downstream sessions and derived tokens are closed before considering the agent retired.
Threat narrative
Attacker objective: The objective is to retain persistent access through an agent credential that remains usable after the organisation believes it has been rotated or revoked.
- Entry begins when an AI agent is issued a credential with broader scope or longer life than the task actually requires, creating an access path that is easier to reuse than to govern.
- Credential access becomes a storage problem when the secret is hardcoded, pasted into configuration, or left in a workflow definition that multiple systems can read.
- Escalation occurs when the same credential is reused across tools or generates downstream tokens that outlive the original control point.
- Impact follows when revocation is assumed to be complete even though cached sessions, derived tokens, or downstream authorisations remain active.
Breaches seen in the wild
- OneLogin API flaw (CVE-2025-59363): A OneLogin API flaw exposed OIDC client secrets to anyone with an API key, including vendors (CVE-2025-59363); fixed with no customer impact.
- iOS apps leaking hard-coded secrets: Cybernews found 71% of 156,080 iOS apps leak hard-coded secrets, with open cloud storage and Firebase databases exposing user data.
Read our 52 NHI Breaches Analysis report for a comprehensive view of breaches impacting Non-Human Identities including AI Agents.
NHI Mgmt Group analysis
Continuous credential lifecycle is the right unit of control for AI agents: issuance, storage, rotation, and revocation fail when each is owned as a separate checklist. The article's core lesson is that an agent credential cannot be governed safely if the identity graph is fragmented across tools and teams. Practitioners should treat the credential's life as one record from creation to confirmed retirement.
Periodic review assumptions do not hold at agent speed: quarterly access reviews assume a credential persists long enough to be reviewed, certified, and remediated. That assumption fails when AI agents can be spun up, used, and retired inside operational cycles shorter than the review cadence. The implication is that lifecycle control has to move to issuance and runtime governance, not just recertification.
Secret storage is now an authorisation problem as much as a hygiene problem: when a credential sits in code, workflow logic, or a container image, the storage location becomes part of the trust boundary. That is not just leakage risk, it is an access-design failure that makes later revocation incomplete by default. Security teams need to treat storage decisions as identity decisions, not only as secrets hygiene.
Revocation without downstream validation creates a false closure state: marking a credential inactive is not the same as removing the access it already enabled. Cached sessions, secondary tokens, and trusted downstream systems can keep the agent effectively alive after the primary secret is disabled. The governance gap is the assumption that one revocation event equals complete retirement, and that assumption is no longer reliable.
Task-scoped AI credentials sharpen the boundary between NHI governance and human IAM: human lifecycle controls can tolerate delay, but AI agent credentials cannot. The named concept here is identity blast radius, which expands whenever an agent holds more scope or duration than the task requires. Practitioners should design for the smallest possible blast radius at issuance, because every later control depends on it.
From our research library:
- Only 20% have formal processes for offboarding and revoking API keys, and even fewer have procedures for rotating them, according to the Ultimate Guide to NHIs.
- 91.6% of secrets remain valid five days after the targeted organisation is notified, showing a critical gap in remediation procedures, according to the Ultimate Guide to NHIs.
- Read next: Ultimate Guide to NHIs
What this signals
Identity blast radius: the most important control question for AI agents is how much access each credential can expose if it leaks or persists longer than intended. The smaller the blast radius at issuance, the less later rotation and revocation have to absorb.
Access reviews built for human cadence do not map cleanly to agent lifecycles. If a credential can be created and retired within the same operational cycle, governance has to shift to issuance-time controls, runtime storage, and downstream revocation checks.
For practitioners
- Tie issuance to agent identity and task scope Require every new AI agent credential to carry an explicit identity, purpose, scope, and expiry before it can be used in production.
- Remove embedded secrets from deployment artifacts Scan repositories, configuration files, workflow definitions, and container images for agent credentials and replace them with runtime retrieval from a governed vault.
- Trigger rotation from lifecycle events Use agent creation, scope change, suspicious access, or tool deprecation as rotation triggers instead of relying on calendar-based resets.
- Verify downstream session closure during revocation Before closing an agent offboarding case, confirm that cached sessions and any secondary tokens minted from the original credential are also invalidated.
- Maintain one continuous credential record Correlate issuance, storage location, rotation status, and revocation evidence in a single identity record so no credential falls between team-owned workflows.
Key takeaways
- AI agent credentials are a lifecycle governance problem, not just a secrets hygiene problem, because issuance, storage, rotation, and revocation all affect the same identity boundary.
- Manual review models miss the pace of agent creation and retirement, leaving credentials active after the organisation has lost track of them.
- The strongest control is not a later cleanup step but a tighter issuance model that limits scope, shortens lifetime, and validates downstream closure.
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 MITRE ATT&CK address the attack and risk surface, while NIST SP 800-53 Rev 5 and NIST CSF 2.0 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-02 — Secret Leakage | The article centers on exposed and misplaced agent credentials. |
| NHI-07 — Long-Lived Secrets | The article argues for short-lived credentials instead of open-ended keys. | |
| NHI-01 — Improper Offboarding | Revocation and retirement are treated as a single lifecycle problem. | |
| Recommendation — Scan agent credential paths for secret leakage and remove embedded secrets from code, images, and workflows. Replace long-lived agent secrets with task-scoped credentials that expire automatically. Validate that agent offboarding closes source credentials, cached sessions, and downstream tokens. | ||
| NIST SP 800-53 Rev 5 | IA-5 — Authenticator Management | Credential issuance, rotation, and revocation are all authenticator lifecycle controls. |
| Recommendation — Apply authenticator management to enforce expiry, rotation triggers, and revocation validation for agents. | ||
| NIST CSF 2.0 | PR.AA-05 — Access Permissions, Entitlements and Authorizations | The article focuses on scoping and governing agent access permissions. |
| Recommendation — Align agent credential scope and entitlement reviews to PR.AA-05 so access stays task-specific. | ||
| MITRE ATT&CK | TA0006; TA0003 — Credential Access; Persistence | Leaked or persistent credentials are the threat pattern the article is addressing. |
| Recommendation — Map agent credential exposure to credential access and persistence techniques to prioritise detections. | ||
Key terms
- AI Agent Credential: An AI agent credential is the proof an autonomous software agent uses to authenticate and act on a system. It can be a token, key, certificate, or delegated identity bound to the agent’s runtime, permissions, and lifecycle, so access can be issued, limited, monitored, and revoked with accountability.
- Credential Lifecycle: Credential lifecycle is the process of issuing, rotating, expiring, and revoking secrets, certificates, and tokens across their usable life. For non-human identities, lifecycle discipline is the core control that separates temporary access from persistent exposure.
- Task-Scoped Credential: A task-scoped credential is a secret or token limited to one specific job, workflow, or short time window. It reduces the chance that an AI agent or automation process can reuse access outside its intended purpose, which is essential when the system can operate continuously or autonomously.
- Downstream Session: An authenticated session or token that remains valid after the original credential has been disabled. For AI agents, downstream sessions matter because revocation is incomplete unless every trusted path created from the original credential is also closed.
What's in the full article
Unosecur's full blog covers the operational detail this post intentionally leaves for the source:
- Specific guidance on how to scope AI agent credentials at issuance without relying on shared service accounts
- Examples of storage failures in repositories, configuration files, and workflow definitions
- Event-triggered rotation patterns for longer-lived agent credentials
- Revocation checks that verify downstream sessions and derived tokens are actually closed
👉 Unosecur's full post covers issuance, storage, rotation, and revocation in more operational detail.
Deepen your knowledge
NHI governance, agentic AI identity, and machine identity lifecycle are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are building or maturing an IAM programme, it is worth exploring.
Published by the NHIMG editorial team on September 30, 2026.
NHI Mgmt Group, the independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org