Security Frameworks for Non-Human Identity: Mapping NIST, OWASP NHI Top 10, and Zero Trust to Machine Credentials

Key Takeaways

• Most security frameworks were written for human users, yet KPMG's latest 80-to-1 NHI ratio shows machines need equal control.
• NIST, Zero Trust, and the OWASP NHI Top 10 each map cleanly onto machine credentials, but only if you treat service accounts and workloads as first-class subjects.
• The OWASP Non-Human Identity Top 10 is the first framework built specifically for machine identities, ranking risks like secret leakage and overprivileged NHIs by real-world impact.
• The 2025 Salesloft Drift breach reached more than 700 organizations through a compromised machine integration, showing why frameworks now have to cover non-human identities directly.

How do security frameworks apply to non-human identities?

Security frameworks apply to non-human identities by extending their existing principles, least privilege, continuous verification, lifecycle governance, and ranked risk, to machine credentials, treating service accounts and workloads as first-class subjects rather than exceptions.

The practical mapping:

• Zero Trust: verify every request, including those from machines, and never trust a credential implicitly.
• NIST controls: apply access control, least privilege, and monitoring to non-human identities, not just users.
• OWASP NHI Top 10: use the first framework built specifically for machine identity risks.
• Identity governance: extend joiner-mover-leaver lifecycle thinking to credentials that are created and abandoned constantly.

Frameworks Mapped to Machine Credentials at a Glance

Each framework contributes a different control, and each maps onto non-human identities in a specific way.

Your security program already runs on frameworks: NIST for controls, Zero Trust for architecture, perhaps a maturity model for governance. Almost all of them were designed around human users who log in, change roles, and leave. The identities those frameworks were built for are now a minority. Non-human identities outnumber people by about 80 to 1, according to KPMG's 2026 cybersecurity reporting, and applying your frameworks to service accounts, workloads, and AI agents is the gap most programs have not closed.

Why do security frameworks need to address non-human identity?

Frameworks encode hard-won lessons about how to reduce risk, but most were shaped by an era when identities meant people. Access reviews, role changes, and offboarding all assume a human lifecycle. Non-human identities break those assumptions. A service account is created by automation, granted broad access, and almost never offboarded. It does not change roles or file access requests.

Scale forces the issue. With machine identities outnumbering humans by 80 to 1, according to KPMG's 2026 cybersecurity reporting, the population that frameworks largely ignore is the larger one. A program that applies its frameworks rigorously to human users and loosely to machines is governing the minority and hoping the majority stays safe.

Breaches make the cost concrete. The 2025 Salesloft Drift incident, documented by Google Threat Intelligence Group, compromised a machine integration and reached more than 700 organizations through stolen tokens. Stolen credentials remain the most common initial access vector in the Verizon Data Breach Investigations Report, and a large share of those credentials belong to non-human identities that frameworks were never explicitly applied to.

How does Zero Trust apply to machine identities?

The Zero Trust security model is built on a single principle: never trust implicitly, always verify. NIST SP 800-207 frames trust as something evaluated on every request rather than granted once. That principle applies to machines as directly as to people, and arguably more urgently, because machine requests vastly outnumber human ones.

In practice, Zero Trust for non-human identities means a valid credential is not enough on its own. This is where intent-based cybersecurity fits: the request still has to be consistent with the identity's declared purpose and behavior. The CISA Zero Trust Maturity Model names non-person entities explicitly as subjects that belong in the identity pillar. A machine identity holding a valid token should still be evaluated against what it normally does, which is exactly how the Salesloft Drift tokens would have stood out: legitimate credentials used in an illegitimate pattern.

How do NIST control frameworks map to non-human identities?

The NIST control families translate directly. NIST SP 800-53 defines access control, least privilege, and continuous monitoring as core controls, and none of them are human-specific. Applied to machines, access control means scoping each machine identity to what it needs, and monitoring means watching credential behavior, not just user logins.

The NIST Cybersecurity Framework adds the higher-level functions, identify, protect, detect, respond, recover, and the first one is where most NHI programs fail. You cannot protect or monitor machine identities you have not identified, and identification is the hardest part precisely because non-human identities are created without oversight. Least privilege is the control that most reduces machine identity risk, and it is the one most often skipped because broad access is the path of least resistance during deployment.

What does the OWASP NHI Top 10 add?

The OWASP Non-Human Identity Top 10 is the first framework written specifically for machine identities, which is why it matters. Rather than adapting human-centric controls, it ranks the risks that are unique to or amplified for non-human identities, drawn from real breaches and vulnerability data.

The 2025 risk list names improper offboarding, secret leakage, overprivileged NHIs, long-lived secrets, and insecure cloud deployment configurations among the top risks. These are exactly the failures that other frameworks gloss over, because a human-centric program rarely asks whether a service account was offboarded or whether a workload token is over-scoped. The OWASP NHI Top 10 gives security teams a ranked, machine-specific checklist that complements the broader frameworks rather than replacing them.

Where do identity governance and CIEM fit?

Identity governance and administration brings the lifecycle discipline: provisioning, periodic review, and deprovisioning. Extending IGA to non-human identities means applying that lifecycle to credentials that appear and disappear at machine speed, which is the work of non-human identity lifecycle governance. The hard part is deprovisioning, because nobody remembers to retire a service account when its workload is gone.

Cloud infrastructure entitlement management (CIEM) supplies the entitlement layer. Frameworks call for least privilege, but you cannot enforce it without knowing what each identity can actually reach. CIEM maps entitlements across cloud environments and flags excess access, turning the abstract framework requirement into a specific list of permissions to remove. Together, IGA and CIEM are how the governance and access-control requirements of every framework get applied to the machine identity population.

How do you turn frameworks into cyber risk mitigation strategies?

Frameworks are only useful when they become operating practice. Turning them into cyber risk mitigation strategies for non-human identities means a few concrete moves: inventory every machine identity, scope each to least privilege against real usage, govern the full lifecycle including deprovisioning, and monitor behavior continuously. Each maps back to a framework, but the value is in the execution, not the citation.

The sequence matters. Discovery comes first, because every other control depends on knowing what exists. Then least privilege, because it produces the largest immediate risk reduction. Then lifecycle governance and continuous monitoring, which keep the program current as the environment changes. A framework that stays a document changes nothing. A framework operationalized against the 80-to-1 majority is what actually reduces risk.

How Token Security approaches non-human identity frameworks

The challenge

Frameworks tell you what good looks like. They do not, by themselves, discover every machine identity across your environment, map what each can reach, or enforce the controls continuously. Applying NIST, Zero Trust, and the OWASP NHI Top 10 to non-human identities requires an operational layer that most programs do not have, and the machine identity population is where that gap is widest.

The approach

Token Security is built for machine identities rather than retrofitted from human IAM. The platform discovers every non-human identity across cloud, SaaS, CI/CD, identity providers, secret vaults, Kubernetes, and AI tooling, then correlates each one to its permissions, its owner, and its behavior, which is the operational foundation every framework assumes. The model is three steps:

• Discover: a live inventory of every machine identity, the prerequisite the NIST identify function and every other framework depend on.
• Understand: entitlement mapping, blast-radius analysis, and behavioral baselines that turn least privilege and Zero Trust from principles into measurable state.
• Enforce: automated remediation and lifecycle governance that apply the OWASP NHI controls and IGA lifecycle to credentials continuously.

The outcome

Frameworks become operating practice instead of documentation. The controls that NIST, Zero Trust, and the OWASP NHI Top 10 call for get applied to the 80-to-1 majority, not just the human minority.

How security teams put this into practice

Treating NHI security as core to the whole program

Frameworks only deliver when machine identity security is treated as part of every security program, not a side project. Udemy framed NHI security as essential across the full range of identities, from legacy systems to AI agents.

"A non-human identity (NHI) solution is quickly becoming an essential tool for modern IT and Engineering environments and a crucial part of every comprehensive security program. Token has built a very strong team and a compelling product that knows how to address these problems."
Chad Kalmes, CISO at Udemy

For a frameworks discussion, the point is scope. The controls in NIST, Zero Trust, and the OWASP NHI Top 10 only reduce risk when they cover every machine identity, across legacy and modern systems alike.

Knowing the full scope before you can govern it

Every framework assumes you know what you are governing, and for non-human identities that assumption usually fails. Elastic described how hard it is to grasp the full scale of the NHI problem before acting on it.

"Non-human identity is a top priority for many teams and it is challenging to gain insight into the full scale and scope of the issue. Token provides an easy solution to get that visibility to then determine where you need to take action."
Mandy Andress, CISO at Elastic

Mapped to frameworks, this is the identify function and the discovery prerequisite in one. You cannot apply any framework to machine identities until you can see the full scope of them, which is where framework adoption has to begin.

The future of machine-first security

Security frameworks are not obsolete in a machine-dominated environment. Their principles, verify every request, enforce least privilege, govern the full lifecycle, and rank risk by impact, apply as directly to service accounts and AI agents as to people. What has changed is the population they must cover. The frameworks were built for the minority, and the minority is now the exception.

The future of machine-first security is applying these frameworks to the identities that actually dominate the environment, treating every machine credential as a first-class subject with an owner, a scope, and a lifecycle. The organizations that operationalize their frameworks against the 80-to-1 majority, rather than citing them while governing only human users, are the ones that close the gap attackers keep exploiting.