Machine identities are the hidden privileged layer IAM still misses

At a glance

What this is: This is an analysis of why machine identities have become a hidden privileged access layer and why traditional identity programmes miss the credentials, ownership, and rotation controls that keep them risky.

Why it matters: It matters because IAM, PAM, and NHI programmes now have to govern workloads, service accounts, and automation with the same discipline once reserved for people.

By the numbers:

• Only 20% have formal processes for offboarding and revoking API keys, and even fewer have procedures for rotating them.
• 96% of organisations store secrets outside of secrets managers in vulnerable locations including code, config files, and CI/CD tools.
• 97% of NHIs carry excessive privileges, increasing unauthorised access and broadening the attack surface.

👉 Read Delinea's analysis of machine identities as a hidden privileged access layer

Context

Machine identities are non-human identities that authenticate and act on behalf of software, workloads, integrations, and automation. The governance gap is that many enterprises still treat them as infrastructure artefacts rather than privileged identities with lifecycles, ownership, and access scope that need active control.

That gap matters because machine identities often accumulate broader access than human users, while their credentials live longer and move faster across cloud stores, code, and operational systems. For IAM and PAM teams, the issue is not count alone. It is whether the organisation can see, rotate, vault, and retire the credentials that make those identities powerful.

Key questions

Q: What breaks when machine identities are not vaulted or rotated?

A: When machine identities are not vaulted or rotated, credentials spread across code, pipelines, and cloud stores become hard to audit and easy to reuse. That makes compromise persistent rather than temporary. The practical consequence is broader blast radius, weaker accountability, and a much higher chance that one credential exposes multiple systems.

Q: Why do machine identities create more privilege risk than many human accounts?

A: Machine identities often run non-interactively, at scale, and with permissions sized for uptime rather than least privilege. Because they can authenticate continuously and accumulate access across systems, their credentials can outlive the workload or owner that created them. That turns access scope into a standing risk unless lifecycle controls are enforced.

Q: How do security teams know if machine identity governance is actually working?

A: It is working when the team can identify every machine identity, name the owner, map the dependency, and show recent rotation or retirement actions. If secrets still live in code or CI/CD, if ownership is unclear, or if high-privilege identities remain untouched for long periods, governance is still incomplete.

Q: Who is accountable when a machine identity credential is compromised?

A: Accountability should sit with the team that owns the workload and the identity platform team that governs the credential lifecycle. Security can set policy, but operational ownership must be clear enough to rotate, vault, or retire the credential without delay. Without that split, machine identity risk becomes everyone’s problem and no one’s job.

Technical breakdown

Why machine identities become a privileged access layer

Machine identities include service accounts, service principals, workload roles, OAuth apps, AI agents, and IAM roles. They authenticate with access keys, secrets, tokens, certificates, and SSH keys, then execute actions across systems without interactive approval. That combination creates a privileged access layer because these identities can be reused at machine speed, often with wider permissions than the tasks require. When ownership is unclear and credentials are scattered, risk is not just exposure. It is durable access that is hard to trace, hard to review, and easy to forget.

Practical implication: build a complete inventory of machine identities and the credentials attached to each one before trying to reduce privilege.

Visibility, posture, and control are the core machine identity mechanics

A workable machine identity programme has three linked stages. Visibility answers what exists, who owns it, and what credentials it uses. Posture assessment identifies high privilege, stale identities, unvaulted secrets, and non-rotated credentials that increase exposure. Control closes the loop with vaulting, rotation, disabling, and least-privilege changes. The important point is sequencing. If you try to control what you cannot contextualise, you risk breaking production. If you only inventory without remediation paths, you simply create a larger report.

Practical implication: organise remediation by visibility first, then posture triage, then controlled credential change.

Why lifecycle management matters more than raw inventory

Machine identity risk persists when credentials outlive the workload or ownership that created them. That is why lifecycle controls matter: provisioning, dependency mapping, rotation, offboarding, and retirement. In practice, the most dangerous identities are often not the newest ones but the forgotten ones with preserved privilege. A hidden privileged access layer becomes manageable only when the programme treats creation, use, and removal as one lifecycle rather than isolated events.

Practical implication: tie every machine identity to an owner, a dependency map, and a retirement condition before it is allowed into production.

Threat narrative

Attacker objective: The objective is to exploit durable machine credentials to gain broad, low-friction access that bypasses interactive human controls.

1. Entry occurs when a machine identity is created with a credential such as an API key, token, or access key that is reused across workloads and stores.
2. Escalation happens when that identity retains broad permissions, remains unrotated, or is not vaulted, allowing the same credential to reach more systems than intended.
3. Impact follows when a compromised or stale machine identity is used to move through cloud services, automation pipelines, or connected applications and expose or alter sensitive assets.

Breaches seen in the wild

• MongoBleed breach — MongoBleed exposed secrets across 87K MongoDB servers.
• IOS app secrets leakage report — iOS apps leaking hardcoded secrets and credentials endangering user privacy.

Read our 52 NHI Breaches Analysis report for a comprehensive view of breaches impacting Non-Human Identities including AI Agents.

NHI Mgmt Group analysis

Machine identity governance fails when organisations treat credentials as plumbing rather than privilege. Delinea’s framing is directionally right, but the deeper issue is that machine identities behave like users while being managed like assets. That mismatch is why ownership, usage, and lifecycle controls break down across cloud, CI/CD, and directory services. The practitioner conclusion is straightforward: machine identity governance has to sit inside identity, not beside infrastructure.

Hidden privileged access is the right concept for this problem because it names the real failure mode. The risk is not that organisations have too many objects. The risk is that high-value credentials remain active in places where no one is accountable for their continued use, including code, config files, and cloud stores. That creates privilege creep with no clear offboarding trigger. Practitioners should measure success by reducing unmanaged privilege, not by shrinking inventory alone.

Visibility is necessary but not sufficient without dependency-aware control. A machine identity can be correctly discovered and still be unsafe to change if the programme cannot map what depends on it. That is why the operational problem is not just finding secrets, but understanding which workload, service, or task will fail if a credential is rotated or retired. The implication is that IAM and PAM teams need dependency context before they can safely enforce control.

NHI governance must now cover machine identities at the same discipline level as human access. The article correctly points to vaulting, rotation, cleanup, and governance, but the field still underestimates how many machine identities carry admin-equivalent privilege. When credentials outlive their purpose, accountability weakens and blast radius grows. Practitioners should reframe machine identity management as privileged access governance across the full lifecycle.

Continuous review models are only useful if the identity remains observable long enough to act on. In machine identity estates, the governance assumption is that access can be found, assessed, and then changed without breaking production. That assumption fails when credentials are embedded in automation, reused across systems, and hidden in unowned stores. The implication is that lifecycle governance, not isolated remediation, is the control model that has to hold.

From our research:

• 96% of organisations store secrets outside of secrets managers in vulnerable locations including code, config files, and CI/CD tools, according to 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.
• That is why the NHI Lifecycle Management Guide is the next step for teams that need provisioning, rotation, and offboarding controls to match the risk.

What this signals

Hidden privileged access: machine identities are becoming a governance problem because the credentials that power them are frequently invisible to the teams responsible for reviewing access. With 1 in 4 organisations already investing in dedicated NHI security capabilities, the market is moving from awareness to operational control, and identity programmes will be measured on whether they can reduce unmanaged privilege rather than merely enumerate it.

The programme signal for IAM and PAM leaders is clear: treat machine identity lifecycle management as a standing operational discipline, not a quarterly cleanup project. Where secrets still live in code and CI/CD, remediation has to start with dependency mapping and vaulting before rotation and retirement can be made safe. The right operating model is discover, contextualise, then control.

Practitioners should also align machine identity governance with the NIST Cybersecurity Framework 2.0 so discovery, protection, detection, and recovery each have an owner for machine credentials and workload access. That alignment becomes more important as service accounts, OAuth apps, and workload roles continue to outnumber the human identities they support.

For practitioners

• Map machine identities to owners and dependencies Create an inventory that ties each service account, workload role, app registration, and secret to a business owner and a dependency map. Do not approve remediation until you can see what workload or service would fail if the credential changes.
• Prioritise the highest-risk credential classes first Start with unvaulted, non-rotated, over-privileged, stale, and shadow machine identities. These are the identities most likely to create broad impact if compromise occurs, and they are usually the fastest path to risk reduction.
• Move high-impact credentials into governed storage Vault API keys, tokens, certificates, and SSH keys that currently live in code, config files, CI/CD systems, or cloud stores. Centralised storage gives you auditability, rotation control, and a clean place to enforce retirement.
• Rotate before you retire Change credentials in the safest order, then disable or retire only after dependencies are validated. This avoids turning access cleanup into an outage event and makes production-safe remediation repeatable.

Key takeaways

• Machine identities now operate as a hidden privileged layer, which makes ownership, visibility, and lifecycle control the real governance challenge.
• The evidence points to persistent exposure, with secrets often stored in unsafe locations and left valid long after they should have been rotated or retired.
• Teams should prioritize vaulting, dependency-aware rotation, and offboarding of the highest-risk machine identities before trying to optimise the rest of the estate.

Key terms

• Machine Identity: A machine identity is a non-human identity used by software, workloads, integrations, or automation to authenticate and act. It usually relies on secrets, tokens, certificates, or keys. In governance terms, it is an identity that must be owned, scoped, rotated, and retired like any other privileged actor.
• Hidden Privileged Access Layer: Hidden privileged access layer describes machine identities that hold powerful permissions but are not managed with the same scrutiny as human privileged accounts. The layer is hidden because the credentials are embedded in systems and workflows, which makes exposure persistent unless lifecycle and vault controls are in place.
• Credential Sprawl: Credential sprawl is the spread of secrets, keys, and tokens across code, config files, CI/CD tools, cloud stores, and ad hoc repositories. It increases the number of places where access can leak and makes rotation, revocation, and audit harder to perform consistently.
• Dependency-Aware Rotation: Dependency-aware rotation is the practice of changing a credential only after mapping what relies on it and confirming the service will keep working. It is a production-safety control as much as a security control, because unmanaged rotation can create outages as easily as it reduces risk.

Deepen your knowledge

NHI governance, agentic AI identity, and machine identity security are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are building or maturing an identity programme, it is worth exploring.

This post draws on content published by Delinea: Manage machine identities as the hidden privileged access layer you need to manage. Read the original.