Machine identities are the new insiders in enterprise governance

At a glance

What this is: This analysis argues that machine identities have become an insider-risk class because they hold legitimate, often high-privilege access while remaining outside human-centric governance models.

Why it matters: IAM, NHI, and PAM teams need to treat machine identities as governed subjects across the full lifecycle, or privilege drift, audit gaps, and orphaned access will keep expanding.

By the numbers:

• More than 70% of cloud privileges are assigned to non-human entities such as service accounts, bots, and APIs.
• Machine identities outnumber human users in most enterprises and 77% represent potential compromise points.

👉 Read SafePaaS's analysis of machine identity governance and insider risk

Context

Machine identity governance is the discipline of discovering, classifying, reviewing, and revoking access for non-human identities such as service accounts, bots, APIs, and certificates. In this article, the core problem is that enterprise IAM still centres human joiner-mover-leaver processes, while machine access now carries a large share of production privilege.

That gap matters because machine identities often operate with legitimate credentials and automated trust, which makes them easy to overlook and hard to audit. When governance is manual or fragmented, orphaned accounts, hardcoded credentials, and privilege sprawl become persistent access risks rather than isolated exceptions.

Key questions

Q: How should security teams govern machine identities across cloud and on-prem environments?

A: Security teams should govern machine identities with the same lifecycle discipline used for human access, but with ownership, scope, and expiry tied to the system rather than the employee. That means inventorying accounts, assigning an accountable owner, limiting privilege, reviewing actual use, and removing access when the process or application ends.

Q: Why do machine identities increase insider-risk exposure?

A: Machine identities increase insider-risk exposure because they authenticate legitimately, operate inside trusted systems, and often hold access that is broader than their actual task. When one is compromised or forgotten, it can act like an insider path for data theft, privilege escalation, or persistence without triggering the same human-focused controls.

Q: What breaks when service accounts are left outside lifecycle governance?

A: When service accounts sit outside lifecycle governance, they become orphaned, overprivileged, and difficult to audit. Teams lose visibility into why they exist, who owns them, and whether their permissions still match the workload. That creates hidden access paths that can survive long after the original business need has ended.

Q: Who is accountable for machine identity risk under zero trust?

A: Accountability sits with the teams that own the workload, platform, or integration using the identity, not with the identity itself. Zero trust requires continuous verification, but governance still needs ownership, review, and revocation. If no team can explain the access, the control has already failed.

Technical breakdown

Why machine identities become invisible insiders

Machine identities behave like insiders because they authenticate with valid credentials, reach internal systems directly, and often run privileged workflows without the behavioural signals associated with a person. They do not need social engineering to blend into the environment. Instead, their legitimacy comes from being embedded in pipelines, integrations, and application logic. That creates a structural blind spot: the identity is trusted, but its purpose, scope, and owner are often unclear. In practice, the control failure is not only exposure of the credential. It is the lack of lifecycle context that tells defenders whether the access still belongs in the environment.

Practical implication: inventory machine identities with owner, purpose, and expiry data, not just credential status.

Privilege sprawl and orphaned service accounts

Privilege sprawl occurs when bots, service accounts, and integrations accumulate permissions across multiple environments over time. Orphaned accounts are the natural end state when short-lived projects, vendor links, or scripts outlive the business need that created them. Because these identities are rarely subject to the same certification cadence as human accounts, access can persist long after the original use case has disappeared. That persistence matters more than raw account count. A small number of forgotten identities can still provide broad lateral access, especially when they are shared, over-scoped, or hardcoded into automation.

Practical implication: tie every non-human account to an owner, a review cadence, and a documented retirement trigger.

Continuous policy enforcement for machine and AI identities

Static IAM controls struggle when the access subject is an automated identity moving through dynamic environments. Policy-based governance matters here because the control has to evaluate function, context, and access intent continuously rather than at a single provisioning moment. For machine identities, that means access should be granted for the task, reviewed against actual use, and removed when the purpose ends. For AI-enabled workflows, the same principle extends to agent activity, where delegated access and action logging become essential evidence. The core architectural shift is from periodic approval to continuous entitlement control.

Practical implication: enforce contextual policies that narrow access based on function, environment, and observed usage.

Threat narrative

Attacker objective: The objective is to use legitimate machine access as a stealthy insider path for persistence, data theft, or broader privilege abuse.

1. Entry occurs when a machine identity is created with excessive privilege, hardcoded credentials, or no clear lifecycle owner, allowing trusted access into production systems.
2. Escalation follows as the identity accumulates permissions or is reused across services, creating lateral movement potential inside cloud and application layers.
3. Impact appears when compromised or unmanaged credentials are used to exfiltrate data, create backdoors, or silently expand access across connected systems.

Breaches seen in the wild

• Sisense breach — unauthorized GitLab access led to exfiltration of access tokens, API keys and certificates.
• Cisco DevHub NHI breach — IntelBroker exploited exposed Cisco credentials, API tokens and keys in DevHub.

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 identities are now a governance subject, not an operational footnote. Once service accounts, APIs, and bots carry the majority of cloud privilege, the identity programme can no longer treat them as implementation detail. The control question changes from "are accounts provisioned" to "are non-human identities owned, reviewed, and retired on purpose." That shift belongs in IAM, PAM, and NHI governance together, because the blast radius comes from access persistence, not account type.

Human-centric lifecycle controls break when the identity is a machine. Joiner-mover-leaver, access certification, and recertification were designed around people with predictable employment states and review windows. Machine identities do not follow that model, so a process built for human cadence will miss orphaned service accounts and unused credentials until after a problem surfaces. The practitioner conclusion is straightforward: lifecycle governance must be re-scoped to the actor type, not simply copied across from HR identity processes.

Privilege drift is the named failure mode hiding inside automation. The article describes a pattern where automation accumulates access faster than governance can re-baseline it. That is not just excess privilege, it is an identity blast radius that grows through reuse, static secrets, and weak ownership. The implication is that governance teams need to measure privilege against current purpose, not original design intent, because machine identities tend to outlive the business conditions that justified them.

Zero trust does not remove the need for machine identity governance. It depends on it. If every transaction is identity-bound, then the verifier must know whether the caller is a person, a bot, an API, or a service account, and must apply least privilege continuously. In that sense, machine identity governance is the operational layer that makes zero trust real for automated systems. Practitioners should treat continuous validation and auditability as baseline requirements, not add-ons.

AI agents intensify the same machine identity problem rather than replacing it. The article groups AI agents with bots and service accounts for a reason: once a non-human actor can execute actions in production, the governance model has to track its permissions, scope, and evidence trail. That convergence means identity teams should stop drawing hard lines between machine identity and emerging agentic workflows. The practical conclusion is to extend one governance model across all non-human actors, then differentiate by autonomy only where the behaviour truly changes.

From our research:

• More than 70% of cloud privileges are assigned to non-human entities such as service accounts, bots, and APIs, according to The 52 NHI breaches Report.
• 77% of machine identities represent potential compromise points in most enterprises, according to CyberArk’s State of Machine Identity Security Report.
• For the next step, see Top 10 NHI Issues for the controls teams most often miss when machine identities scale faster than governance.

What this signals

Privilege drift is becoming the defining machine-identity signal. As automation spreads, the question is no longer whether non-human accounts exist, but whether their access still matches the purpose they were created for. The practical response is to move from periodic account checks to continuous entitlement reconciliation, with lifecycle ownership attached to every service account, bot, and API credential.

A useful programme concept here is identity blast radius: the amount of damage a single non-human identity can cause when its access outlives its original job. Teams should measure that blast radius by privilege breadth, credential age, and the number of systems reachable from one identity, then reduce it before audit or incident response proves the gap.

Machine identities now sit squarely inside zero-trust design, not beside it. That means governance teams should align their access policies with continuous verification, short-lived privilege, and evidence-rich logging, while using the NIST Cybersecurity Framework 2.0 to structure control ownership across protect, detect, and respond functions.

For practitioners

• Inventory every machine identity with an owner Create a live register for service accounts, API keys, bots, and certificates that records business owner, technical owner, purpose, environment, and retirement date. Anything without an accountable owner should be treated as governance debt, not a harmless leftover.
• Remove standing privilege from automated accounts Re-scope non-human access to the smallest viable permission set and separate routine task access from elevated admin functions. Where access must remain high risk, require explicit approvals and short-lived elevation rather than permanent entitlements.
• Retire orphaned credentials on a fixed cadence Tie service-account retirement to project closure, vendor offboarding, and pipeline decommissioning. Build expiry checks into the workflow so credentials cannot outlive the system or business process that created them.
• Bring machine identities into access reviews Include non-human identities in certification campaigns and review the actual usage pattern, not just the existence of the account. Reviewers should be able to confirm why the identity still exists, what it touches, and who will remove it if the answer is no longer valid.
• Log and reconcile every privileged action Link machine identity actions to business functions and retain evidence of privilege changes, approvals, and abnormal usage. This is the audit trail compliance teams need when they are asked to prove control over automated access.

Key takeaways

• Machine identities have become a major insider-risk class because they hold legitimate access outside the human governance model.
• The evidence points to scale, not edge cases, with cloud privilege concentrated heavily in non-human identities and many of them still unmanaged.
• The control answer is lifecycle governance for every non-human identity, backed by ownership, least privilege, and continuous review.

Key terms

• Machine Identity: A machine identity is a credentialed non-human subject such as a service account, API key, bot, certificate, or workload identity. It authenticates systems and automation rather than people. In governance terms, it must still have ownership, scope, review, and retirement just like any other access subject.
• Privilege Drift: Privilege drift is the gradual expansion of access beyond what a workload, bot, or service account originally needed. It happens when permissions accumulate through reuse, exceptions, and forgotten dependencies. The result is a wider blast radius than the business process requires, which makes compromise more damaging.
• Orphaned Account: An orphaned account is a non-human identity that remains active after the project, application, vendor relationship, or workflow that created it has ended. These accounts are especially dangerous because they often retain valid credentials but no clear owner, which makes review and removal slow or unlikely.
• Continuous Access Certification: Continuous access certification is the practice of reviewing privilege as part of ongoing operations rather than at a single periodic checkpoint. For machine identities, that means evidence must reflect real usage, current purpose, and business ownership. It is the governance bridge between automation speed and auditability.

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

This post draws on content published by SafePaaS: machine identities are the new insiders in enterprise governance. Read the original.