TL;DR: Machine identities now outnumber human users in modern enterprises, according to SecurEnds, while traditional IAM was built for stable human accounts rather than dynamic service accounts, API keys, and workload identities. Governance has shifted from provisioning to ownership, lifecycle control, auditability, and continuous monitoring at machine speed.
At a glance
What this is: This is an analysis of why machine identity governance has become a control gap in IAM as cloud, automation, and AI expand the number and scope of non-human identities.
Why it matters: It matters because IAM programmes that still centre on people will miss ownership, privilege, and lifecycle risk across service accounts, API keys, certificates, and workload identities.
Context
Machine identity governance is the control layer that assigns ownership, visibility, access boundaries, and lifecycle oversight to non-human identities such as service accounts, API keys, certificates, bots, and workload identities. The problem is no longer simply how to issue credentials, but how to govern identities that are created continuously across cloud, DevOps, APIs, containers, and AI-driven systems.
SecurEnds frames the gap as a mismatch between legacy identity governance models and the speed of machine identity creation. When credentials appear dynamically and may exist only for a short workload window, manual review cycles, spreadsheet tracking, and human-centric ownership models lose operational relevance quickly.
The article treats machine identity governance as a necessary extension of IAM, not a separate discipline. That is the right framing for enterprises trying to keep auditability, privilege control, and accountability intact as non-human access becomes the default operating model.
Key questions
Q: What breaks when machine identities are governed separately from human IAM?
A: Separate governance creates blind spots in entitlement review, revocation, and monitoring. A machine identity can retain broad access long after the business need changes, and teams may never see it inside the human access review cycle. That leaves runtime access outside normal oversight.
Q: Why do machine identities create more risk than human identities in some environments?
A: Machine identities are often numerous, long-lived, and embedded in code or infrastructure. They are harder to review manually, easier to overlook during offboarding, and more likely to carry excessive privilege. That combination increases blast radius when a secret or token is exposed.
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: What should IAM teams do when service account access is broader than the workload needs?
A: IAM teams should reduce the entitlement to the minimum runtime function the workload requires and then revalidate the dependency with the technical owner. Broad service account access usually persists because teams optimise for deployment convenience, not governance. Tightening scope reduces blast radius and makes later audit and offboarding decisions far easier.
Technical breakdown
Why machine identity governance is different from IAM
Machine identity governance adds policy, inventory, ownership, and review discipline on top of provisioning and authentication. Traditional IAM assumes a bounded human population, predictable joiner-mover-leaver events, and review cadences that can keep pace with people. Machine identities break those assumptions because they are generated by pipelines, orchestration, and application workflows, often with no obvious business owner. Governance therefore has to operate across discovery, entitlements, monitoring, and lifecycle evidence, not just account creation.
Practical implication: treat service accounts, API keys, and workload identities as governed assets, not just authentication artefacts.
Why ownership and auditability fail at machine speed
Ownership is the core governance problem because a credential without a responsible owner cannot be recertified, retired, or justified. In machine environments, developers, platform teams, and automation systems may all create access paths faster than governance teams can map them. That creates audit gaps, orphaned identities, and permissions that persist after the workload or integration has changed. The operational issue is not only scale, but the loss of an accountable human decision point for each non-human identity.
Practical implication: require both technical and business ownership for every machine identity before it is allowed to persist.
How least privilege changes for service accounts and workload identities
Least privilege for machine identities is not a one-time role assignment. It depends on restricting blast radius, limiting credential lifespan, and narrowing access to the exact system, API, or workload the identity needs. Because machine identities often exist to support automation, teams tend to over-grant permissions to avoid broken deployments. That convenience becomes a security debt when credentials are reused, left dormant, or left active across multiple environments. Governance must therefore enforce access scope and usage review continuously.
Practical implication: design privilege boundaries around the workload, not around the team that created the identity.
Threat narrative
Attacker objective: The objective is to exploit weakly governed non-human identities to move through cloud and application environments with minimal detection and excessive access.
- Entry occurs when machine identities are created faster than governance teams can inventory them, especially through CI/CD pipelines, APIs, and cloud automation.
- Credential exposure follows when long-lived secrets, certificates, or tokens are left active beyond the workload they were meant to support.
- Privilege misuse escalates the problem when overprivileged service accounts or API keys can reach multiple systems or cloud services.
- Impact appears as hidden access, weak audit trails, and expanded blast radius when a compromised or orphaned machine identity is abused.
Breaches seen in the wild
- Dropbox Sign breach 2024: A compromised back-end service account gave attackers Dropbox Sign customer data, including API keys, OAuth tokens and MFA information.
- 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.
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 is now an IAM control gap, not an adjacent hygiene problem. The article correctly shows that non-human identities now sit inside core enterprise workflows, from cloud automation to API-driven access. Once machine identities outnumber human accounts, governance based on human operating assumptions stops reflecting the real access model. The implication is that IAM programmes must treat non-human ownership, entitlement scope, and lifecycle evidence as first-class controls.
Ownership is the decisive control in machine identity governance. A service account or API key without accountable ownership cannot be certified, retired, or explained during audit. That is why orphaned identities are not just an inventory issue, but a governance failure that breaks accountability across technical and business teams. The practical conclusion is that identity programmes need explicit ownership states, not implied responsibility.
Long-lived machine credentials create a governance debt that compounds faster than human review cycles can clear. The article's emphasis on rotation and continuous monitoring reflects a real shift in control design. Governance cannot rely on periodic reviews alone when credentials are created dynamically and may survive beyond the workload that generated them. The conclusion is that auditability must be built into issuance, not bolted on afterward.
Least privilege for non-human identities must be defined around workload scope, not organisational structure. Traditional role design often mirrors teams and departments, but machine identities exist to execute narrow technical functions. Overprivilege happens when broad permissions are granted for deployment convenience and then never reduced. The conclusion is that machine identity governance has to measure entitlement scope against runtime function, not against who requested the access.
AI agents and automated workloads should be governed as machine identities until their autonomy is truly proven. The article touches on AI agents as governed identities, which is the right baseline for most current deployments. Many organisations will call a system autonomous before they have actually validated independent decision authority, tool selection, and execution timing. The conclusion is to govern the identity first, then reassess the autonomy model as behaviour matures.
From our research library:
- NHIs outnumber human identities by 25x to 50x in modern enterprises, according to the Ultimate Guide to NHIs.
- Read next: Ultimate Guide to NHIs
What this signals
Machine identity governance becomes a programme design issue once non-human access scales faster than human review. Security teams should assume that inventory lag is now a structural risk, not an implementation flaw. The control shift is toward continuous discovery, ownership validation, and lifecycle evidence that can keep up with cloud-native creation rates.
Identity governance programmes that stop at employee access reviews are leaving a material gap. Service accounts, API keys, certificates, and workload identities need the same certification logic as human accounts, but with tighter dependence on automated discovery and revocation workflows. That is where the operating model has to change first.
Credential rotation alone is not enough to govern machine identities well. Rotation reduces exposure, but it does not solve the deeper problem of who owns the identity, why it exists, and whether it should exist at all. Those questions define whether the programme has governance or just maintenance.
For practitioners
- Map every non-human identity to a named owner Build a governance register that assigns both technical and business ownership to service accounts, API keys, certificates, bots, and workload identities before they are allowed to remain active.
- Replace spreadsheet tracking with continuous discovery Continuously discover machine identities across cloud, SaaS, Kubernetes, serverless, and CI/CD environments so orphaned or duplicated credentials do not escape review.
- Constrain machine privileges to workload scope Remove convenience-based entitlements and define access only for the systems and APIs the workload must reach, then recertify those permissions on a recurring basis.
- Automate rotation for exposed credentials Use short-lived credentials and automated rotation for secrets, tokens, and certificates that support automation or privileged service access.
- Extend access reviews to machine identities Include service accounts, API credentials, workload identities, bots, and automation accounts in certification cycles so standing access is not left outside governance.
Key takeaways
- Machine identity governance is now a core IAM control issue because cloud automation has pushed non-human identities into the centre of enterprise access.
- The main failure mode is not a single missing control, but the lack of ownership, auditability, and lifecycle discipline for machine credentials.
- IAM teams should move governance upstream into issuance, scope, and review so machine identities do not become persistent blind spots.
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 addresses the attack and risk surface, while NIST CSF 2.0 and CIS Controls v8 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-05 — Overprivileged NHI | Excess machine permissions are a central risk in this article. |
| NHI-01 — Improper Offboarding | Dormant and orphaned machine identities are a major governance gap here. | |
| NHI-07 — Long-Lived Secrets | The article stresses short-lived credentials and rotation for machine access. | |
| Recommendation — Reduce machine identity entitlements to the minimum runtime scope and recertify them regularly. Track non-human identity ownership through offboarding and revoke credentials when dependencies end. Replace long-lived machine credentials with short-lived secrets and automated renewal workflows. | ||
| NIST CSF 2.0 | PR.AA-05 — Access Permissions, Entitlements and Authorizations | The article centres on governance of machine entitlements and access scope. |
| Recommendation — Apply entitlement review and authorisation controls to non-human identities as part of access governance. | ||
| CIS Controls v8 | CIS-5 — Account Management | Machine identity inventory, ownership, and lifecycle control map directly to account management. |
| Recommendation — Use account management processes to inventory, validate, and retire machine identities. | ||
Key terms
- Machine Identity Governance: Machine Identity Governance is the discipline of controlling how non-human identities are created, used, monitored, and retired. It covers service accounts, API keys, certificates, tokens, workloads, and automation identities, with policies for ownership, lifecycle, least privilege, rotation, attestation, and auditability across cloud, application, and infrastructure environments.
- Orphaned Machine Identity: An orphaned machine identity is a service account, token, or similar credential that no longer has a clear owner or active business purpose. These identities are high-risk because they often retain access, evade review, and become persistent entry points after the system or team that created them has changed.
- Credential Sprawl: Credential sprawl is the uncontrolled accumulation of machine secrets, keys, and tokens across systems, teams, and environments. It usually starts with a single use case and ends with overlapping permissions, unclear ownership, and a larger attack surface than the organisation expected.
- Workload Identity: The identity assigned to a software workload, such as a containerised application, serverless function, or microservice, enabling it to authenticate to other services without storing static credentials.
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.
Published by the NHIMG editorial team on July 1, 2026.
Updated on October 6, 2026.
NHI Mgmt Group, the independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org