TL;DR: Compliance frameworks still assume human users and miss the machine identities that now drive cloud access, data movement, and audit evidence, according to Token Security. Without visibility into service accounts, API keys, bots, and containers, organisations cannot prove least privilege, custody, or regulatory scope.
At a glance
What this is: This is an analysis of why human-centric compliance breaks down when machine identities control most cloud operations and audit evidence.
Why it matters: IAM, IGA, PAM, and NHI teams need visibility into machine identities because compliance claims collapse when access, custody, and scope cannot be tied to a specific non-human actor.
Context
Compliance programmes often fail at the point where human-focused controls meet machine-driven reality. Traditional audit evidence assumes a named employee, a manager, and a stable access review cycle, but cloud workloads, service accounts, and API keys do not behave that way.
Machine identity visibility is the missing layer. When auditors cannot see which non-human identities exist, what they can access, and how long that access persists, compliance becomes a paper exercise rather than a governance control.
The article argues that this is not a documentation gap. It is a structural mismatch between frameworks built for people and environments now dominated by NHI activity.
Key questions
Q: What breaks when compliance programmes are built only around human users?
A: They fail to account for machine identities that create, move, and use access outside human review cycles. The result is incomplete inventory, weak evidence, and audit scope that excludes the highest-risk credentials. A programme can look mature on paper while remaining blind to the identities actually controlling cloud data and workloads.
A: Machine identities create risk because they often scale faster than human oversight, while certificate lifecycles, privileges, and ownership can drift over time. In regulated environments, that drift weakens accountability, makes audits harder, and increases the chance that old credentials remain valid after they should be removed or rotated. Automation is the main control that narrows that gap.
Q: What are the signs that a compliance programme has blind spots in machine identity governance?
A: Common signs include incomplete service account inventories, tokens found outside central identity systems, audit samples that cover only known accounts, and logs that name a token but not the workload behind it. Those signals indicate the organisation is governing a subset of access rather than the real machine identity estate.
Q: How should teams prove custody for regulated data accessed by bots or service accounts?
A: They need contextual audit trails that connect the credential to the workload, repository, environment, and accountable team. Without that chain, logs show activity but not custody, which is not enough for compliance, forensics, or internal accountability. The evidence must make the non-human actor traceable end to end.
Technical breakdown
Why human-centric access reviews fail for machine identities
Most compliance frameworks inherit a user model: a person has an account, a manager reviews access, and privileges change slowly enough to be sampled. Machine identities break that model because they are numerous, ephemeral, and often created outside central identity systems. A service account may exist only to support a workflow, yet it can hold standing privilege that no manager ever sees. That makes the review process incomplete even when the paperwork is perfect. The technical issue is not that reviewers are inattentive. It is that the subject being reviewed is not a human identity at all.
Practical implication: treat machine identities as first-class audit subjects, not exceptions hidden inside human access review workflows.
Why bearer tokens and ephemeral workloads undermine proof of least privilege
In cloud-native environments, access is frequently expressed through bearer tokens, OAuth grants, and short-lived workload credentials rather than interactive logins. That changes the evidentiary model. Least privilege cannot be demonstrated by showing a policy on paper if the workload can mint, reuse, or inherit broader access at runtime. Ephemeral containers and serverless functions also complicate attestation because the identity may exist for minutes, but the permissions can outlive the instance. Without runtime visibility, the compliance team can describe intent but cannot prove effective control.
Practical implication: validate least privilege at issuance and runtime, not only through quarterly access certification.
How shadow machine identities create audit scope gaps
A central compliance failure is incomplete inventory. Organisations often catalogue the service accounts visible in their main identity provider while missing identities created directly in cloud platforms, SaaS tools, CI/CD pipelines, and code repositories. Those hidden credentials form a shadow layer of access that is outside the formal control set, which means the auditor samples the wrong population. Once scope is incomplete, every downstream attestation is weakened. The environment may look controlled on the report, but the report is only measuring the managed subset, not the actual access estate.
Practical implication: build discovery across cloud, code, and SaaS to close the gap between declared scope and actual machine access.
Threat narrative
Attacker objective: The attacker or uncontrolled workload objective is to use hidden machine access to reach sensitive data while remaining outside governance and audit scope.
- Entry occurs when machine identities are created through cloud integrations, code repositories, or SaaS connections that bypass central visibility.
- Credential access then persists through hardcoded API keys, bearer tokens, and standing service account privileges that are not rotated or inventoried.
- Escalation follows when those identities are used to access regulated data, move information across regions, or extend access into systems outside the intended compliance boundary.
- Impact is a failed audit posture and a broken chain of custody, because the organisation cannot prove who or what accessed sensitive data.
Breaches seen in the wild
- Salesloft OAuth token breach: hackers stole OAuth tokens to access Salesforce data via Salesloft.
- Sisense breach 2024: A credential in Sisense's GitLab reportedly opened S3 buckets of customer tokens, passwords and certificates; CISA urged a full reset.
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 visibility is a compliance prerequisite, not an operational nice-to-have. Human-centric frameworks can only govern what they can identify, enumerate, and review. Once service accounts, API keys, and workload credentials outnumber employees and move faster than annual audits, the control model changes from review to discovery. The implication is that compliance programmes must start from a complete machine identity inventory before they can claim any meaningful assurance.
Shadow access is the real non-compliance layer. The formal directory rarely contains the full population of cloud-native identities, so the organisation attests to a subset while the highest-risk credentials sit outside scope. That is a governance failure, not an evidence-collection issue. The practical conclusion is that the scope definition itself has to include unmanaged machine identities, or the audit result is structurally incomplete.
Continuous visibility changes the meaning of least privilege. For machine identities, privilege cannot be inferred from provisioning state alone because actual use can diverge immediately from intended use. The control becomes an observable behaviour problem, not a static permissions problem. Practitioners should therefore treat runtime telemetry as part of the compliance evidence chain, not as a separate security function.
Audit readiness now depends on machine custody chains. If a token, service account, or bot can touch regulated data, the organisation needs to tie that action back to a workload, a repository, and an accountable owner. Without that context, access logs record activity but not custody. The implication is that identity governance and data governance are converging around the same machine identity evidence set.
Machine identity visibility should be the named control objective for cloud compliance programmes. The article exposes a specific gap that deserves its own vocabulary: machine identity visibility debt. That is the backlog of unmanaged or unobserved non-human access paths that make every other control harder to prove. Practitioners should use that concept to frame remediation around evidence completeness, not just policy enforcement.
From our research library:
- Only 5.7% of organisations have full visibility into their service accounts, according to the Ultimate Guide to NHIs.
- Read next: Service Account Security Guide
What this signals
Machine identity visibility debt: most compliance failures in cloud-native environments are not caused by missing policies, but by unmanaged non-human access paths that never enter the evidence chain. Once that debt accumulates, auditors can only verify the subset of access the organisation already knows about.
Identity governance teams should assume that every hidden service account or token widens the gap between declared scope and actual control. That gap is where compliance, security, and data-custody failures converge.
The immediate programme question is no longer whether machine identities exist. It is whether they are enumerable, attributable, and continuously reviewed as part of the compliance control set.
For practitioners
- Map the full machine identity estate Discover service accounts, API keys, tokens, certificates, bots, and cloud workload identities across IdP, cloud platforms, CI/CD, and SaaS integrations.
- Replace sample-based reviews with continuous evidence Move machine identity governance from quarterly spreadsheet checks to automated monitoring of creation, privilege changes, usage, and revocation.
- Tie every sensitive-data access path to an accountable workload Record which workload, repository, team, and business process owns each non-human credential that can reach regulated data.
- Audit shadow access outside the main directory Search cloud-native and SaaS-native permission stores for identities that never pass through the corporate IdP and reconcile them into scope.
Key takeaways
- Human-centric compliance models miss the access layer now run by machine identities, so a clean audit can coexist with weak governance.
- The article’s evidence is practical rather than theoretical: only 5.7% of organisations have full visibility into their service accounts.
- Compliance teams need continuous machine identity discovery and contextual evidence if they want to prove least privilege, custody, and scope.
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 surface, NIST CSF 2.0 and CIS Controls v8 set the technical controls, and ISO/IEC 27001:2022 defines the regulatory obligations.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-02 — Secret Leakage | The article ties compliance failure to hardcoded API keys and other unobserved machine credentials. |
| NHI-05 — Overprivileged NHI | Standing privileges for bots and service accounts are central to the article's least-privilege critique. | |
| Recommendation — Scan repositories and cloud estates for leaked machine secrets and bring them into compliance scope. Right-size machine access based on observed use and remove excessive standing privilege. | ||
| NIST CSF 2.0 | PR.AA-05 — Access Permissions, Entitlements and Authorizations | The article is about proving that access permissions for NHIs are known and controlled. |
| Recommendation — Validate entitlements for machine identities continuously, not only during periodic review cycles. | ||
| CIS Controls v8 | CIS-5 — Account Management | Account inventory and lifecycle management are the article's core control gaps. |
| Recommendation — Inventory, review, and retire machine accounts as part of account management governance. | ||
| ISO/IEC 27001:2022 | A.5.15 — Access control | The post argues that access control fails when non-human identities are invisible to the ISMS. |
| Recommendation — Document and enforce access control for machine identities inside the ISMS evidence set. | ||
| MITRE ATT&CK | TA0006;TA0008 — Credential Access; Lateral Movement | Exposed tokens and overprivileged machine identities support credential abuse and downstream movement. |
| Recommendation — Map hidden machine credentials to credential-access and lateral-movement detections. | ||
Key terms
- Machine Identity: The digital identity of a machine, device, or workload, such as a server, container, or VM, used to authenticate it within a network. Sometimes used interchangeably with NHI, though NHI is the broader category.
- Shadow Access: Shadow access is unauthorised or unmanaged access that continues to exist because a credential, role, or account was forgotten, reused, or never properly revoked. In NHI programmes, shadow access is especially dangerous because it can remain active across cloud, SaaS, and automation layers without obvious human ownership.
- Chain of custody: A documented record that preserves the integrity of evidence from the moment an event is detected through investigation and response. In identity and data protection workflows, it helps prove what happened, when it happened, and which actor or session was involved.
- Standing Privilege: Standing privilege is access that remains active even when no immediate task requires it. For NHI programmes, it is a common failure mode because long-lived credentials and persistent roles create unnecessary exposure. Reducing standing privilege usually means tighter expiry, on-demand access, and clearer review of who or what still needs access.
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 May 30, 2026.
Updated on October 6, 2026.
NHI Mgmt Group, the independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org