Many organisations assume SSO and PAM cover the whole identity stack, but they mainly govern sign-ins and privileged sessions. They do not automatically discover every API key, token, service account, or AI agent secret spread across SaaS, code, and automation. Without broader oversight, credential sprawl continues even when core access controls look mature.
Why This Matters for Security Teams
SSO and PAM are essential, but they solve a narrower problem than many teams assume: authenticated user access and tightly governed privileged sessions. They do not automatically map, inventory, or revoke the full set of machine and application credentials that actually power modern systems. That gap matters because the real attack surface includes API keys, service accounts, tokens, certificates, CI/CD secrets, and agent credentials spread across SaaS, code repositories, and automation.
When organisations treat SSO and PAM as a complete control plane, credential sprawl stays hidden until a breach, a failed audit, or an exposed secret in source control forces the issue. The Guide to the Secret Sprawl Challenge shows how often secrets escape the perimeter of traditional identity tooling, while the OWASP Non-Human Identity Top 10 frames the risk as an identity governance problem, not just a privileged access problem. In practice, many security teams discover the gap only after a token is abused in automation, rather than through intentional credential lifecycle control.
How It Works in Practice
SSO governs how humans authenticate into applications, and PAM governs how high-risk privileged sessions are brokered, recorded, and sometimes approved. That is valuable, but it does not extend to every credential type that machines use to talk to other machines. A service account in Kubernetes, an API key in a SaaS integration, a token in a CI/CD workflow, or an AI agent secret in an orchestration layer may never touch SSO or PAM at all.
Practically, this means teams need a broader control model that starts with discovery and ends with automated lifecycle management. Current guidance from NHI security research and standards suggests a few patterns:
- Inventory every non-human credential, including embedded secrets, ephemeral tokens, and certificates.
- Classify credentials by workload, owner, environment, and blast radius.
- Move from static secrets to short-lived credentials where possible, with clear TTLs and automated revocation.
- Use policy-based access decisions for workloads, not just interactive users.
- Monitor where secrets appear in code, pipelines, SaaS, and agent tooling.
This is where Ultimate Guide to NHIs is useful, because static vs dynamic secrets changes the operational model entirely. NIST’s Digital Identity Guidelines remain important for human identity assurance, but they do not replace workload identity governance. For that reason, many organisations pair discovery tooling with workload-aware controls, secret rotation, and tighter release gates, rather than expecting SSO and PAM to police secrets they never see. When credentials are deeply embedded in legacy apps, third-party integrations, or autonomous workflows, the model breaks down because revocation becomes manual, brittle, and too slow for operational reality.
Common Variations and Edge Cases
Tighter credential control often increases operational overhead, requiring organisations to balance security gains against deployment friction, service uptime, and developer workflow speed. That tradeoff becomes sharper in hybrid environments where legacy systems cannot easily support ephemeral credentials or modern workload identity.
There is no universal standard for every environment yet, but best practice is evolving toward layered governance. Some teams keep PAM for human-admin access while using separate controls for machine identities. Others extend policy-as-code and secret scanning into CI/CD, then add runtime attestation for workloads that can support it. In agentic systems, the problem is even more acute because autonomous tools may request new credentials dynamically, making static approval workflows too slow.
The most common mistake is assuming one control plane covers all identities. In reality, SSO and PAM are necessary but insufficient. The 2024 Non-Human Identity Security Report notes that 88.5% of organisations say their NHI practices lag behind or merely match human IAM, which fits the pattern of overconfidence in familiar controls. Where teams also rely on a CI/CD pipeline exploitation case study or secret-sprawl review, the lesson is consistent: the edge case is not rare, it is simply outside the scope of traditional sign-in and session tooling.
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, OWASP Agentic AI Top 10 and CSA MAESTRO address the attack and risk surface, while NIST AI RMF 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-01 | Addresses missing inventory of non-human credentials beyond SSO and PAM. |
| OWASP Agentic AI Top 10 | A-03 | Relevant where AI agents use secrets outside normal human sign-in flows. |
| CSA MAESTRO | M1 | Covers workload identity and policy for autonomous or service-based identities. |
| NIST AI RMF | Supports governance for AI systems that consume and expose credentials dynamically. | |
| NIST CSF 2.0 | PR.AC-4 | Least-privilege access management is central to reducing secret sprawl risk. |
Bind agent actions to short-lived workload credentials and revoke them after each task.
