If agents already have persistent credentials, rotate and revoke those secrets first because they are the fastest path to compromise. If the agents perform high-impact actions, add approval workflows next. The best order is usually remove standing trust, then constrain what the agent can do in real time.
Why This Matters for Security Teams
The sequencing question matters because secrets rotation and agent approval workflows solve different failure modes. Rotation removes exposed or stale credentials, while approvals constrain what an agent can do when it still has valid access. For autonomous workloads, standing credentials are often the most immediate compromise path, which is why this question sits at the intersection of Guide to the Secret Sprawl Challenge and the broader governance issues described in the OWASP Non-Human Identity Top 10. Once those credentials are live, approval gates do not stop misuse of an already-issued token.
That is especially true when agents have tool access, can chain actions, or operate across SaaS, CI/CD, and cloud control planes. The better sequence is usually to reduce the blast radius first, then add runtime friction where the action itself is risky. Current guidance from NIST AI Risk Management Framework and OWASP Agentic AI Top 10 supports that layered view: identify the highest-probability compromise path first, then govern high-impact execution. In practice, many security teams discover the wrong priority only after a leaked token has already been used to complete an unintended agent action.
How It Works in Practice
Start with secrets rotation when agents rely on persistent API keys, service account passwords, or long-lived tokens. Those credentials are reusable, hard to contain, and often copied into places that outlive the original task. Rotating them first breaks the easiest path to unauthorized reuse. The next step is to move away from static trust altogether by issuing dynamic secrets, short-lived tokens, and workload identity patterns that better fit machine actors.
For agents that can initiate changes, approvals should be applied to the action, not just the identity. That usually means intent-based or context-aware authorisation at runtime, where the policy engine checks what the agent is trying to do, what data it touches, and whether the request is within the current task boundary. Controls inspired by CSA MAESTRO agentic AI threat modeling framework and the NIST AI Risk Management Framework are useful here because they emphasise context, accountability, and impact.
- Use rotation to remove standing trust and invalidate exposed secrets first.
- Issue JIT, ephemeral credentials per task where the platform supports it.
- Bind agent access to workload identity rather than shared human credentials.
- Require approval only for actions with material blast radius, such as deletions, transfers, or policy changes.
- Log every approval, denial, and credential issuance for audit and incident response.
NHIMG research shows why this matters: 44% of NHI tokens are exposed in the wild, sent or stored in collaboration tools, tickets, pages, and code commits in The 2025 State of NHIs and Secrets in Cybersecurity. These controls tend to break down when agents are given shared service accounts and broad cross-system permissions because the approval layer cannot reliably distinguish routine automation from dangerous escalation.
Common Variations and Edge Cases
Tighter approval workflows often increase latency and operator overhead, requiring organisations to balance responsiveness against reduction in blast radius. That tradeoff is real, especially for production agents that trigger frequent but low-risk actions. In those environments, best practice is evolving toward tiered approvals: no approval for routine read-only tasks, lightweight approval for reversible actions, and strong human or policy-backed approval for destructive or externally visible actions.
There is no universal standard for this yet, but the emerging pattern is to avoid making human approval the first line of defence when secrets are still static. If the environment includes CI/CD pipelines, multi-agent workflows, or service-to-service orchestration, the priority may shift further toward workload identity, ephemeral secrets, and rotation practices that can actually keep up with machine speed. NHI lifecycle management is the more durable fix when the agent population is large, because NHI Lifecycle Management Guide makes clear that access creation, use, rotation, and revocation must be treated as one continuous control loop.
Edge cases also arise when approvals are used to compensate for weak identity design. If the same NHI serves multiple applications or the agent can self-select tools without strong policy enforcement, approvals become a patch rather than a control. In those cases, organisations should first eliminate standing secrets, then enforce real-time policy checks through OWASP Agentic AI Top 10 aligned controls and workload-scoped identity.
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 AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-03 | Rotation and revocation of exposed NHI secrets is the first-line fix. |
| OWASP Agentic AI Top 10 | A2 | Agentic systems need runtime controls for tool use and harmful actions. |
| NIST AI RMF | AI RMF supports governance, accountability, and context-aware risk decisions. |
Rotate standing secrets first, then move high-risk agents to short-lived credentials.
