Secrets and NHI convergence is reshaping identity security

At a glance

What this is: This analysis says secrets management and non-human identity management are converging into one governance problem as machine identities, credentials, and privileged access multiply.

Why it matters: It matters because IAM, PAM, and NHI teams can no longer treat credentials, lifecycle, and runtime access as separate domains if they want consistent control over non-human access.

By the numbers:

• Non-human identities outnumber human identities by 25x to 50x in modern enterprises.

👉 Read Akeyless's analysis of secrets management and non-human identity convergence

Context

Secrets management and non-human identity management are now converging because the same machine identity often depends on passwords, API keys, certificates, tokens, and runtime permissions at the same time. When those controls are managed separately, organisations create gaps between credential storage, identity ownership, and access governance.

This matters most in cloud-native and automated environments, where service accounts, workloads, CI/CD pipelines, and AI systems all authenticate without direct human involvement. The primary issue is not simply more identities, but a governance model that was built for people and vaults rather than for machine-led access patterns.

Key questions

Q: How should security teams govern secrets and machine identities together?

A: Security teams should govern them as one lifecycle problem. The credential, the identity, and the runtime permission should all have the same owner, the same revocation path, and the same audit trail. If those elements are split across different teams or tools, exposure lasts longer and accountability becomes harder to prove.

Q: Why do machine identities create more risk than stored secrets alone?

A: Machine identities create more risk because they can reuse credentials across multiple systems, carry excessive privileges, and persist after the workload or application changes. A stored secret is only one part of the risk. The larger issue is whether that secret still authorises access in places the organisation no longer expects.

Q: What breaks when secret rotation is treated as a standalone control?

A: Rotation alone breaks when teams do not also handle ownership, offboarding, and entitlement review. A rotated secret can still belong to a forgotten service account, and a revoked secret can still leave another credential active. Effective control comes from tying rotation to lifecycle state, not treating it as a separate hygiene task.

Q: Who is accountable when a machine credential exposes privileged access?

A: Accountability should sit with the business or platform owner that created or approved the machine identity, supported by IAM, PAM, and security operations. If no owner can explain why the identity exists, what it can access, and when it should be removed, the governance model is already failing.

Technical breakdown

Why secrets and machine identity controls are collapsing into one layer

Secrets management historically focused on protecting credentials at rest, while non-human identity management focused on governing which machine or service could use them. That separation breaks down when the same service account, token, or certificate both proves identity and authorises runtime access. In cloud and DevOps environments, access is often short-lived, distributed across tools, and tied to automation that can create or consume credentials at machine speed. The result is that storage control alone does not equal identity control, and identity control alone does not secure the credential itself.

Practical implication: treat credential storage, identity ownership, and runtime access as one control surface.

How machine identities create lifecycle and privilege governance problems

Machine identities are frequently created dynamically, reused across applications, and left active long after the workload or integration changes. That creates lifecycle failure, privilege creep, and audit blind spots because the same access path can survive well beyond its original purpose. In practice, this means rotation, offboarding, and entitlement review are not optional housekeeping tasks. They are the only way to keep non-human access aligned with business reality. Without lifecycle discipline, secrets management becomes a storage problem while governance problems accumulate elsewhere.

Practical implication: map every machine identity to an owner, lifecycle state, and revocation path.

What zero trust means for secrets, certificates, and privileged access

Zero trust for non-human identities means assuming that every credential can be discovered, copied, or reused unless access is continuously constrained. That puts more emphasis on ephemeral credentials, policy-based authorisation, and explicit boundaries for privileged actions. It also means privileged access cannot be treated as a separate human-only domain, because service accounts and automation often hold the same sensitive rights as administrators. A unified model is required to prevent credentials from becoming standing privilege in disguise.

Practical implication: verify that machine access is short-lived, least-privilege, and observable before production deployment.

NHI Mgmt Group analysis

Secrets management and non-human identity management are now the same governance problem. The old split between vaulting credentials and governing machine access was designed for a world where storage and identity could be controlled separately. That assumption fails when a service account, certificate, or token is both the credential and the identity itself. The implication is that lifecycle, privilege, and runtime access now have to be assessed together, not in separate silos.

Machine identity sprawl creates identity blast radius, not just inventory noise. As applications, APIs, pipelines, and workloads multiply, one exposed secret can map to many downstream services and shared entitlements. That is why machine identity governance is no longer a narrow NHI task, but a core IAM and PAM concern as well. Practitioners should treat each shared credential as a potential blast-radius multiplier rather than a simple asset count problem.

Unified control planes are becoming the default expectation for modern identity security. Organisations are moving toward architectures that can govern secrets, certificates, encryption keys, and privileged access through the same policy model. That shift does not eliminate specialist tools, but it does change the standard for acceptable fragmentation. The practical conclusion is that teams should re-evaluate whether their current stack can actually enforce one ownership and revocation model across all machine identities.

91.6% of secrets remain valid five days after the targeted organisation is notified, according to our Ultimate Guide to NHIs. That gap shows how slowly many remediation processes move relative to machine access exposure. The implication is that response cadence, not just detection quality, is a central control issue for NHI governance.

From our research:

• 91.6% of secrets remain valid five days after the targeted organisation is notified, according to Ultimate Guide to NHIs.
• Only 5.7% of organisations have full visibility into their service accounts, according to Ultimate Guide to NHIs.
• For a broader breach lens, see 52 NHI Breaches Analysis for the recurring failure patterns that turn unmanaged machine access into incidents.

What this signals

Identity blast radius: when one machine credential is reused across multiple systems, the risk is no longer limited to a single secret leak. Teams should expect wider containment needs, faster revocation requirements, and more pressure to prove ownership across IAM, PAM, and secrets tooling.

The practical signal for programmes is that inventories alone are not enough. If your organisation cannot connect a machine identity to an owner, a lifecycle state, and a revocation event, then governance is still incomplete even if the secret store looks healthy.

A useful benchmark for prioritisation is visibility. Only 5.7% of organisations have full visibility into their service accounts, according to Ultimate Guide to NHIs, which means most teams will need to improve discovery before they can improve policy enforcement.

For practitioners

• Unify ownership for machine credentials Assign a named owner to every service account, token, certificate, and key so secrets management and identity governance do not drift into separate queues.
• Tie rotation to lifecycle events Rotate and revoke credentials when applications change, integrations move, or workloads are retired, rather than relying on calendar-only rotation rules.
• Audit standing privilege in machine access paths Review whether non-human identities hold persistent rights that should be short-lived, task-scoped, or policy-mediated at runtime.
• Consolidate audit evidence across secrets and identity tools Make sure audit logs, ownership records, and revocation events can be correlated across vaults, IAM systems, and CI/CD pipelines.

Key takeaways

• Secrets management and NHI governance are converging because machine identities now depend on credentials, lifecycle controls, and privileged access at the same time.
• The scale problem is already material, with non-human identities outnumbering human identities by 25x to 50x in modern enterprises.
• Practitioners should move from isolated credential storage to unified ownership, rotation, and revocation across the full machine identity lifecycle.

Key terms

• Non-Human Identity: A non-human identity is any digital identity used by software, services, workloads, or automation rather than a person. It includes service accounts, API keys, tokens, certificates, and AI systems that authenticate and act inside enterprise environments.
• Secrets Management: Secrets management is the practice of protecting, distributing, rotating, and revoking credentials that systems use to authenticate. In modern environments, it must be tied to identity lifecycle and access policy, or stored secrets can remain active long after they should have been removed.
• Machine Identity Lifecycle: Machine identity lifecycle is the full process of creating, owning, rotating, reviewing, and retiring non-human identities and the credentials they depend on. The control only works when offboarding and revocation happen as reliably as provisioning.
• Standing Privilege: Standing privilege is access that remains continuously available instead of being issued only when needed. For machine identities, standing privilege increases blast radius because the credential can be reused, shared, or abused long after its original task is complete.

What's in the full article

Akeyless's full article covers the operational detail this post intentionally leaves for the source:

• KuppingerCole category criteria for secrets management and non-human identity leadership
• Akeyless's platform capabilities across secrets, certificates, keys, and privileged access
• The vendor's own explanation of Distributed Fragments Cryptography and zero-knowledge architecture
• Examples of cloud, DevOps, and automation integrations discussed in the source article

👉 The full Akeyless article covers the KuppingerCole findings, platform scope, and machine identity governance context.

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 responsible for identity security strategy or NHI governance in your organisation, it is worth exploring.