TL;DR: Machine identities now outnumber human users by 25 to 50 per person in many organisations, and the article argues that zero trust remains incomplete unless APIs, workloads, bots, and devices are authenticated, authorised, and continuously monitored with lifecycle controls, according to Token Security. The core issue is that machine trust assumptions break when identities are created, rotated, and deactivated at machine speed.
At a glance
What this is: NHI Mgmt Group's analysis, drawing on Token Security's blog post: Zero trust for machine identities only works when machine credentials, access decisions, and lifecycle events are governed continuously rather than treated as static accounts.
Why it matters: IAM, PAM, and NHI teams need to account for machine identities as a primary trust boundary because unmanaged service accounts, API keys, and certificates create hidden access paths across cloud and hybrid estates.
By the numbers:
- Machine identities now outnumber human users by 25 to 50 per person in many organisations.
Context
Zero trust for machine identities is a governance problem before it is a tooling problem. The article's core claim is that identity, not network location, becomes the control boundary once workloads, APIs, bots, containers, and devices begin authenticating to one another at scale.
That shifts the IAM question from who a user is to how non-human identities are issued, scoped, rotated, and retired. If machine identities are managed as static assets, zero trust coverage becomes partial and the trust model leaves blind spots across cloud, SaaS, and hybrid environments.
Key questions
Q: What breaks when machine identities are excluded from Zero Trust policy?
A: Zero Trust breaks when machine identities are excluded because service accounts and workloads often generate the highest-volume internal access. If those identities are governed differently from human users, attackers can exploit the gap through over-privileged service access, weak logging, or unmanaged integrations. The policy model becomes incomplete.
Q: What problem does ownership attribution solve for service accounts and API keys?
A: It closes the gap between exposure detection and accountable remediation. Many organisations can find the secret, but not the human who introduced it, maintains it, or can safely replace it. Ownership attribution gives security teams a practical way to assign action without relying on informal knowledge that disappears during staff changes.
Q: How do teams know whether machine identity controls are actually working?
A: Look for complete inventory coverage, clear ownership, regular credential rotation, and the ability to revoke access quickly without breaking dependent services. If identities still rely on spreadsheets, shared secrets, or manual exception handling, the control environment is not working at enterprise scale. The signal to watch is whether access can be governed without emergency intervention.
Q: What should teams do when machine identity policy is spread across many tools?
A: Consolidate governance around one identity-first policy model so the same machine receives the same authorization outcome everywhere. Fragmented policy creates gaps that over-permissioned service accounts, expired certificates, and shadow identities can exploit.
Technical breakdown
How machine identity changes the zero trust perimeter
In a machine-heavy environment, the perimeter is no longer the subnet or host boundary. It is the set of identity assertions a workload presents at request time, including certificates, tokens, mTLS sessions, and policy context. That means every API call, service-to-service invocation, and device request depends on identity proof, authorization scope, and runtime posture, not on network placement. The article's point is that zero trust only remains coherent when machine identity is treated as a first-class trust primitive, with policy decisions applied continuously instead of once at provisioning.
Practical implication: move access control for machines into identity-aware enforcement points such as gateways, service meshes, and policy engines.
Why lifecycle management is central to machine trust
Machine identities differ from human accounts because they are created automatically, often live briefly, and frequently lack clear owners. That creates a lifecycle problem: credentials must be provisioned, rotated, and deactivated at machine speed or they become orphaned, stale, or reused. The article highlights this in the context of certificates, API keys, and short-lived tokens. Without lifecycle automation, zero trust becomes a snapshot of intent rather than an operating model, because the identity may outlive the workload it was meant to secure.
Practical implication: govern machine identity lifecycle events as operational controls, not after-the-fact audit tasks.
Where fragmented policy creates hidden trust gaps
The article points to policy rules scattered across IAM, cloud platforms, Kubernetes, device managers, and API gateways. Fragmentation matters because zero trust relies on consistent decisions about the same identity across every environment and control plane. If one tool treats a service account as privileged and another treats it as ordinary, the resulting access model is inconsistent and exploitable. The technical failure is not absence of policy, but mismatch between policy domains, which lets over-permissioned service accounts, hardcoded secrets, and expired certificates persist.
Practical implication: consolidate machine identity policy decisions so scoping, monitoring, and revocation follow one governance model.
Threat narrative
Attacker objective: The attacker aims to use trusted machine credentials to reach internal services and data without triggering controls built for human users.
- Entry begins with exposed API keys, unmanaged service accounts, hardcoded secrets, or expired certificates that attackers can reuse as legitimate machine credentials.
- Escalation follows when over-permissioned service accounts or fragmented policy rules let the attacker move from one machine identity to broader service access.
- Impact comes through lateral movement and hidden access paths across cloud, SaaS, or hybrid environments, where stale credentials continue to function after the original workload changes or disappears.
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.
- Massive Docker Hub Secrets Leak: 10,000+ Docker Hub container images expose hardcoded secrets and authentication keys.
Read our 52 NHI Breaches Analysis report for a comprehensive view of breaches impacting Non-Human Identities including AI Agents.
NHI Mgmt Group analysis
Zero trust is incomplete when machine identities are treated as secondary actors. The article shows that workloads, APIs, bots, containers, and devices now make access decisions that matter as much as human logins. Once that happens, the trust boundary shifts from user authentication to machine identity governance. Practitioners need to treat machine identity as a primary control plane, not an edge case.
Lifecycle control is the decisive machine trust discipline. Machine identities are created, rotated, and retired faster than human access review cycles can observe them. That is why provisioning, rotation, and deactivation belong in the trust model itself. The practical conclusion is simple: if lifecycle is not automated, zero trust becomes a policy statement rather than an enforced boundary.
Shadow machine identities create the widest zero trust gap. Hardcoded secrets, copied certificates, unmanaged API keys, and unsanctioned bots bypass formal ownership and therefore bypass accountability. The control problem is not just visibility, it is governance over identities no one claims. Teams should assume that the riskiest machine access is often the access no inventory currently records.
Fragmented policy undermines continuous verification. The article describes machine trust decisions being spread across tools that do not share a common view of privilege or posture. That fragmentation weakens contextual authorization and makes revocation inconsistent. The implication for IAM and PAM teams is that machine identity governance has to be policy-coherent across platforms, or zero trust will fracture at integration points.
Machine identity now belongs inside the zero trust operating model. The article reinforces a broader market shift: identity governance for non-human entities is no longer a specialised subtopic. It is becoming the mechanism through which cloud, SaaS, device, and workload trust is actually enforced. Practitioners should expect machine identity governance to converge with broader access, lifecycle, and runtime controls.
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 — Why NHI Security Matters Now
What this signals
Machine identities outscale human identity programmes. At 25x to 50x per user, machine credentials change the size of the governance problem more than the shape of the existing IAM stack. That is why lifecycle automation, not just stronger authentication, becomes the control that prevents machine trust from dissolving into sprawl, according to the Ultimate Guide to NHIs.
Zero trust for machines fails at issuance time, not only at breach time. When credentials can be created and retired faster than review processes can observe, the governance model has to move upstream to issuance, policy scoping, and automated deactivation. Teams that keep reviewing machine access after the fact are measuring a state that may already be gone.
For practitioners
- Map machine identities as a governed inventory Record service accounts, API keys, certificates, bots, workloads, and device identities in one ownership model so trust decisions can be applied consistently.
- Automate rotation and deactivation Replace manual renewal and offboarding steps with automated certificate renewal, token regeneration, and immediate identity removal when workloads disappear.
- Enforce least privilege for every machine request Scope each identity to a single workflow, endpoint, or dataset and remove broad access that creates hidden lateral movement paths.
- Unify policy across control planes Align IAM, cloud, Kubernetes, API gateway, and device policies so the same machine identity receives the same authorization outcome everywhere.
Key takeaways
- Machine identities are not a side issue in zero trust, because they now carry a volume of access that can exceed human identity by orders of magnitude.
- The biggest control weakness is not a single missing tool, but the combination of unmanaged credentials, fragmented policy, and weak lifecycle governance.
- Practical zero trust for machines depends on automated issuance, rotation, revocation, and consistent authorization across every control plane.
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 and MITRE ATT&CK address the attack and risk surface, while NIST Zero Trust (SP 800-207) and NIST CSF 2.0 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-05 — Overprivileged NHI | Over-permissioned service accounts are named as a hidden attack path in the article. |
| NHI-07 — Long-Lived Secrets | The article stresses rotation of certificates, tokens, and API keys as central to machine trust. | |
| NHI-01 — Improper Offboarding | Immediate deactivation is required when ephemeral workloads disappear or identities become orphaned. | |
| Recommendation — Review machine access scopes and remove standing privilege that exceeds each identity's job function. Shorten credential lifetimes and automate rotation for machine secrets that outlive their workload. Revoke and remove machine identities as soon as the workload or service they support is retired. | ||
| NIST Zero Trust (SP 800-207) | Zero Trust Policy Decision Point — Policy Decision Point | The article relies on continuous identity-aware decisions across many control planes. |
| Recommendation — Centralise trust decisions so machine identity posture is evaluated consistently at every access request. | ||
| NIST CSF 2.0 | PR.AA-05 — Access Permissions, Entitlements and Authorizations | Least privilege and contextual authorization are central to machine zero trust in the article. |
| Recommendation — Align machine permissions to the minimum entitlements needed for each access path and workflow. | ||
| MITRE ATT&CK | TA0006;TA0008 — Credential Access; Lateral Movement | The article describes exposed keys and over-permissioned accounts as paths to broader service access. |
| Recommendation — Map exposed machine secrets to credential-access and lateral-movement detections in your threat model. | ||
Key terms
- Machine identity lifecycle: Machine identity lifecycle is the full governance process for a non-human identity from creation to retirement. It includes provisioning, access scoping, rotation, renewal, offboarding, and auditability, and it fails when any one of those steps is handled manually or inconsistently.
- Continuous Verification: A Zero Trust practice that re-evaluates trust during the session instead of relying on a single successful login. The control is stronger when context signals are available in real time and when the identity programme can act on those signals without creating excessive exceptions.
- Shadow Machine Identity: A shadow machine identity is a credential or account that exists and can authenticate, but is not visible to security teams through normal governance processes. These identities are dangerous because they often retain excessive access, bypass review, and persist long after the workload that created them has changed.
- Context-Aware Authorization: Context-aware authorization evaluates signals such as device posture, time, resource sensitivity, and request type before allowing access. It moves IAM away from static permission checks and toward decisions that reflect current risk, which is essential in cloud-native environments with frequent identity changes.
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 building or maturing an IAM programme, it is worth exploring.
Published by the NHIMG editorial team on July 6, 2026.
Updated on October 6, 2026.
NHI Mgmt Group, the independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org