TL;DR: Machine-to-machine interactions now run core enterprise assets without human intervention, and SailPoint argues that traditional IAM and PAM controls were built for human identities rather than unmanaged non-human identities. The governance gap is no longer theoretical, because lifecycle, discovery, and credential controls have to cover machine identities as first-class citizens.
At a glance
What this is: This is an analysis of why machine identities are becoming a first-class IAM problem, with the central finding that human-built IAM and PAM controls leave non-human identities under-governed.
Why it matters: IAM, IGA, PAM, and DevSecOps teams need to redesign governance for non-human identity lifecycles, because machine access now scales faster than human review cycles.
Context
Machine identity security is now an IAM governance problem, not just a technical hygiene issue. Machines and workloads are continuously authenticating, connecting, and acting against enterprise assets without human intervention, which means the identity model itself has shifted.
The gap is structural: human-centric IAM and PAM processes were built around people, while non-human identities are provisioned, monitored, and retired in fragmented ways. Once those identities become the dominant runtime actors, lifecycle control and credential governance become core security controls rather than support functions.
Key questions
Q: What breaks when organisations manage machine identities like user accounts?
A: The programme loses visibility, ownership, and lifecycle control. Machine identities do not follow human onboarding, MFA, or password-reset patterns, so user-first processes miss the real control points. That leads to orphaned credentials, weak attribution, and a larger attack surface than the access review process is able to detect.
Q: Why do long-lived machine credentials increase breach risk?
A: Long-lived credentials create a standing access path that can survive code changes, personnel changes, and forgotten integrations. Once exposed, they can be replayed for as long as they remain valid. That makes them more dangerous than narrowly scoped, short-lived credentials because the attacker has more time to find, test, and abuse them.
Q: How do security teams know whether machine identity governance is working?
A: They know it is working when every non-human credential has a named owner, a visible system scope, and a documented retirement path. If access reviews cannot answer when the identity was last used or why it still exists, governance is only partial. High confidence comes from evidence of cleanup, not just policy coverage.
Q: What should IAM teams prioritise as identity programmes scale?
A: IAM teams should prioritise observability, reversibility, and policy enforcement over simply adding more workflows. Scale increases the chance that edge cases, fallback logic, and deprovisioning overlaps will create hidden risk. A mature programme can show who requested access, who approved it, when it expires, and how it is removed.
Technical breakdown
Why machine identity sprawl breaks human-centric IAM
Machine identities are non-human identities that authenticate workloads, services, APIs, and automated processes. Traditional IAM assumes a stable user with a bounded access pattern, but machine identities are numerous, ephemeral in some cases, and often created outside central governance. That makes discovery, ownership, and retirement materially harder than for human accounts. When these identities accumulate across cloud, DevSecOps, and infrastructure layers, the result is identity sprawl: access paths that exist, work, and persist without a clear lifecycle owner. Practical implication: treat machine identity inventory as a governance control, not a one-time audit exercise.
Practical implication: move machine identity discovery into an owned governance process with explicit lifecycle accountability.
Why static secrets are the weak point in machine authentication
Many machine identities still rely on long-lived passwords, API keys, or certificates that are difficult to track and easy to reuse. That creates a durable trust problem because compromise of the secret effectively becomes compromise of the identity. The article points toward cryptographic attestation and short-lived credentials as the direction of travel, with SPIFFE and SPIRE as examples of workload identity patterns that reduce secret dependence. The mechanism matters: the workload proves identity at runtime, instead of relying on a secret that can be copied and retained. Practical implication: reduce standing machine credentials wherever runtime proof of identity is possible.
Practical implication: prioritise short-lived, attestable workload credentials over reusable static secrets.
How AI-driven discovery changes machine identity governance
The article describes AI and machine learning as a way to correlate inventories, source code scans, logs, cloud configurations, and network activity to find orphaned or overprivileged NHIs. That matters because machine identities are rarely visible in one control plane. Governance improves when discovery is continuous and cross-source, because ownership, permission scope, and inactivity become observable signals rather than assumptions. This is especially important for shared accounts, orphaned credentials, and access patterns that drift after deployment. Practical implication: use cross-domain telemetry to classify machine identities before you attempt to govern them.
Practical implication: tie discovery to classification so machine identities can be governed before access drift becomes normal.
Threat narrative
Attacker objective: The objective is to use unmanaged machine identity access as a persistent path to enterprise systems and data.
- Entry occurs when machine credentials such as API keys, tokens, or certificates are provisioned and then left in place across environments, making them easy to copy, reuse, or inherit.
- Credential abuse follows when those long-lived identities retain access beyond their intended use, especially where ownership, retirement, or segregation is fragmented.
- Impact occurs when overprivileged or orphaned machine identities continue operating against critical assets and data without timely detection or revocation.
Breaches seen in the wild
- Scania insurance portal breach 2025: An attacker used an external user login, likely stolen by infostealer malware, to take insurance claim documents from a Scania portal.
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 the baseline for modern IAM. The article reflects a broader shift: workloads and services are no longer supporting actors, they are core actors in enterprise access. That means IAM and PAM programmes built around humans no longer describe the real access surface. Practitioners need to treat machine identities as governed identities with their own lifecycle, ownership, and access scope.
Static secret trust debt is the defining risk in machine identity security. Long-lived API keys, passwords, and certificates create a persistence model that is easy to inherit and hard to retire. The problem is not just exposure, but durability: once a secret exists, it keeps extending trust unless someone actively constrains it. That makes short-lived, attestable credentials the strategic direction for reducing machine identity blast radius.
Identity sprawl explosion is the right concept for the current state of NHIs. The article correctly points to the combination of unmanaged identities, fragmented tooling, and weak lifecycle controls as a structural governance failure. The issue is not only volume, but the inability to assign ownership, classify access breadth, and retire identities consistently. Practitioners should read this as a governance maturity gap, not a tooling selection problem.
Convergence of human and non-human governance will reshape identity architecture. The article suggests that IGA, IAM, PAM, ISPM, and ITDR will increasingly overlap around a single identity plane. That convergence is happening because policy, monitoring, and risk scoring cannot remain split between people and machines when both are acting on the same assets. The implication is that identity architecture will increasingly be judged on how well it governs all identity types together.
From our research library:
- 69% of security leaders agree identity management must fundamentally shift to address agentic AI systems, according to the 2026 Infrastructure Identity Survey.
- Read next: Ultimate Guide to NHIs — Key Challenges and Risks
What this signals
Static secret trust debt: machine identity programmes fail when reusable credentials are allowed to persist longer than the systems that depend on them. The control question is not whether a secret exists, but whether its trust window is shorter than the operational window it protects.
Discovery-before-governance is the new operating model: IAM teams cannot recertify or retire what they cannot see. Machine identities need continuous classification across code, logs, cloud configuration, and runtime activity before lifecycle control becomes credible.
The industry is moving toward a unified identity plane where human, workload, and agent access are governed through the same policy logic. That does not erase the differences between actor types, but it does make fragmented governance harder to justify.
For practitioners
- Define machine identity ownership and retirement Assign a named owner to every workload, service account, API key, token, and certificate, then tie retirement to the application or pipeline that created it.
- Replace long-lived secrets with short-lived credentials Prioritise ephemeral, cryptographically attested credentials where workloads can prove identity at runtime instead of reusing static secrets across environments.
- Centralise discovery across code, logs, and cloud configs Correlate source code scans, cloud configuration, inventory data, and network activity to find orphaned, overprivileged, or shared NHIs before they become routine.
Key takeaways
- Machine identities are no longer edge cases, because they now drive core enterprise interactions at machine speed and scale.
- The main governance gap is structural: fragmented lifecycle control, long-lived secrets, and limited visibility leave NHIs outside traditional IAM and PAM assumptions.
- The practical response is to govern machine identities as first-class identities, with continuous discovery, named ownership, and short-lived credentials.
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 SP 800-53 Rev 5 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-02 — Secret Leakage | The article centres on exposed and reusable machine secrets as a core governance risk. |
| NHI-05 — Overprivileged NHI | It highlights overprivileged and orphaned NHIs created through fragmented lifecycle control. | |
| NHI-07 — Long-Lived Secrets | Long-lived credentials are presented as the main persistence mechanism for machine identity risk. | |
| Recommendation — Scan for exposed machine secrets and revoke any credential that can be copied or reused. Review machine identity entitlements and remove excess access before the next deployment cycle. Replace standing machine credentials with short-lived alternatives wherever the workload supports it. | ||
| NIST SP 800-53 Rev 5 | IA-5 — Authenticator Management | Credential lifecycle management is central to the article's guidance on machine identities. |
| Recommendation — Apply authenticator lifecycle controls to rotate, retire, and replace machine credentials on schedule. | ||
| NIST CSF 2.0 | PR.AA-05 — Access Permissions, Entitlements and Authorizations | The article focuses on governing machine access scope, ownership, and entitlement drift. |
| Recommendation — Define and monitor machine identity authorizations so access remains bounded to current need. | ||
| MITRE ATT&CK | TA0006;TA0008 — Credential Access; Lateral Movement | Unmanaged machine credentials can be abused for credential access and movement across systems. |
| Recommendation — Map exposed machine secrets to credential-access and lateral-movement detections in your threat model. | ||
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.
- Identity Sprawl: Identity sprawl is the uncontrolled growth of identities, entitlements, and credentials across an environment. For NHIs, it usually appears when automation creates accounts faster than governance teams can inventory, review, and remove them. The result is hidden access, weak accountability, and a wider attack surface.
- Short-Lived Attested Credential: A short-lived attested credential is a token or certificate issued for a specific run or workload after the platform verifies who or what is asking. It reduces replay risk because the credential is only useful within a narrow window and is tied to claims that can be checked at runtime.
- Cryptographic Attestation: Cryptographic attestation is a method of proving that a workload or service is genuine by using cryptographic evidence instead of static shared secrets. It is especially useful for short-lived access models because identity proof is tied to runtime context rather than reusable credentials.
Deepen your knowledge
NHI governance, machine identity security, and identity lifecycle management 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 or identity security programme, it is worth exploring.
Published by the NHIMG editorial team on June 24, 2026.
Updated on October 6, 2026.
NHI Mgmt Group, the independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org