Machine identity sprawl is exposing lifecycle gaps in cloud security

At a glance

What this is: This article argues that machine identity growth is outpacing governance, with static secrets, dormant identities, and weak lifecycle control creating avoidable exposure.

Why it matters: It matters because IAM, PAM, and NHI teams have to govern machine access with the same discipline used for human identities, especially as AI agents increase dependence on secrets and privileged service access.

By the numbers:

• Gartner estimates that machine identities outnumber human identities by a ratio of 45 to 1.
• Anecdotal evidence shows that in some organizations, as high as 75% of secrets remain static, significantly increasing the risk of exploitation.
• Cloudflare rotated over 5,000 secrets after the Okta support incident, but four were still missed.

👉 Read Saviynt's analysis of machine identity growth and secret management

Context

Machine identity security is the discipline of governing service accounts, API keys, tokens, certificates, and other non-human credentials that software uses to reach critical resources. In cloud-native environments, those identities now sit at the center of application access, infrastructure automation, and emerging AI agent workflows, which means machine identity governance is no longer a niche control problem.

The governance gap is lifecycle ownership. Many machine identities are created quickly, reused across systems, and left dormant or unrotated, which creates a privilege and secrets management problem that traditional human IAM processes were never designed to absorb. For readers looking to benchmark lifecycle discipline, the Ultimate Guide to NHIs and the NHI Lifecycle Management Guide frame the control problem in more operational terms.

The article's core point is typical of modern infrastructure: identity sprawl is not a side effect of scale, it is a predictable outcome when machine access is created faster than ownership, rotation, and retirement controls can keep up.

Key questions

Q: What breaks when corporate IT machine identities are not lifecycle-managed?

A: What breaks is the assumption that mature infrastructure controls automatically govern non-human access. Service accounts, SSH keys, and embedded credentials can survive migrations and ownership changes, which means access outlives accountability. The practical result is hidden privilege drift, lateral movement paths, and a governance gap that normal reviews do not reliably catch.

Q: Why do machine identities increase lateral movement risk in cloud and SaaS environments?

A: Machine identities often have persistent access, broad integration reach and fewer human friction points than user accounts. If one is compromised, attackers can reuse it across connected systems, admin APIs and automation workflows. That turns a single secret into a path for broader compromise.

Q: How do security teams know if machine identity governance is actually working?

A: It is working when the team can identify every machine identity, name the owner, map the dependency, and show recent rotation or retirement actions. If secrets still live in code or CI/CD, if ownership is unclear, or if high-privilege identities remain untouched for long periods, governance is still incomplete.

Q: How do organisations decide between secretless authentication and rotation?

A: Use secretless authentication wherever the platform and integration allow it, because it removes manual secret handling from the workflow. Where legacy systems block that option, rotation becomes the compensating control, supported by least privilege and monitoring. The decision is not either-or across the estate; it is capability-based by integration.

Technical breakdown

Why static secrets remain the default machine identity pattern

Machine identities frequently authenticate with shared secrets such as API keys, OAuth tokens, or certificates because those credentials are easy to issue and integrate. The problem is that static secrets persist across environments, can be copied into scripts or configuration files, and are hard to trace once reused. When the same credential is valid across multiple systems, the blast radius expands quietly. That makes the secret itself a standing risk object, not just an access mechanism.

Practical implication: treat every reusable secret as a governed asset with ownership, rotation, and retirement state.

How dormant machine identities turn into hidden access paths

Dormant machine identities are credentials or service accounts that still exist but are no longer actively supervised, often because the original use case has changed or disappeared. In distributed cloud and SaaS environments, those identities can retain access long after the business process that created them has moved on. That creates a visibility gap where access continues without operational intent. Lifecycle governance is the only reliable way to surface and remove those paths.

Practical implication: inventory machine identities by purpose and last-use state, then retire anything without a current owner.

Why elevated privileges make machine identity governance harder

Many machine identities need elevated access to perform infrastructure, deployment, or integration tasks, which makes them attractive to attackers and dangerous when over-scoped. Unlike human access, machine privilege is often embedded into runtime workflows, CI/CD pipelines, or application logic, so revocation can break production if the design was never modularised. That is why privilege management for machines has to be tied to dependency mapping, not just credential storage. Without that, rotation may reduce exposure but leave the underlying privilege problem intact.

Practical implication: map each privileged machine identity to the workload dependency it serves before tightening scope or revoking access.

Threat narrative

Attacker objective: The attacker aims to turn exposed machine credentials into persistent, privileged access across systems and environments.

1. Entry begins when secrets are stored in support tickets, scripts, or configuration files where they can be discovered by an attacker or exposed through a third-party system.
2. Escalation follows when those secrets carry elevated access and can be reused across environments, giving the attacker broader reach than the original creator intended.
3. Impact occurs when dormant or static machine identities remain valid long enough for exploitation, allowing unauthorized access to critical resources and potentially sensitive data.

Breaches seen in the wild

• Moltbook AI agent keys breach — Moltbook breach exposed 1.5M AI agent keys.
• Sisense breach — unauthorized GitLab access led to exfiltration of access tokens, API keys and certificates.

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 sprawl is the result of governance lag, not just cloud growth. The article correctly shows that machine identities are multiplying faster than most organisations can assign ownership, monitor usage, and retire stale access. Once a credential can be created by developers, business users, or automated pipelines, lifecycle discipline becomes the real control plane. Practitioners should read this as a machine identity governance problem, not a tooling problem.

Static secrets are not a convenience trade-off, they are a standing exposure window. Secrets stored in applications, tickets, or scripts are copied, reused, and forgotten because the workflow rewards speed over traceability. That means the organisation inherits access that outlives the person or process that created it. The practical conclusion is that secret management must be treated as an identity lifecycle function, not an operational afterthought.

Vendor access without lifecycle offboarding is the named failure mode this article exposes. Cloud and SaaS environments routinely leave machine credentials active after the original purpose changes, which creates unauthorised continuity of access. The article's support-ticket example and missed secret rotation show that offboarding machine access is often incomplete even when teams believe they have contained the issue. Practitioners should recognise this as an accountability gap across the identity chain.

Identity blast radius is the better way to frame machine identity risk than simple credential count. A single static secret may connect multiple applications, environments, and privileges, so the control question is how far one compromised identity can reach. That lens aligns more closely with zero trust and least privilege than raw inventory metrics do. Security teams should use blast radius as the basis for prioritising remediation.

From our research:

• Only 19.6% of security professionals express strong confidence in their organisation's ability to securely manage non-human workload identities, according to the 2024 Non-Human Identity Security Report.
• 88.5% of organisations acknowledge that their non-human IAM practices lag behind or are merely on par with their human identity and access management efforts.
• The NHI Lifecycle Management Guide helps teams turn that confidence gap into an operational programme for ownership, rotation, and offboarding.

What this signals

Machine identity governance is converging with lifecycle management, not sitting beside it. As AI systems and cloud automation expand, organisations will have to treat every machine credential as a live identity with ownership, scope, and retirement state. That shift makes lifecycle tooling and policy enforcement central to identity architecture rather than a back-office hygiene function.

With 70% of organisations granting AI systems more access than they would give a human employee performing the exact same job, per the 2026 Infrastructure Identity Survey, the next governance problem is not just credential sprawl but privilege mismatch. Teams should expect more pressure to prove that machine access is narrowly scoped and continuously reviewed.

The operational question is whether your programme can prove that machine identities are owned, monitored, and retired at the same pace as the systems that depend on them. If not, the identity estate will keep accumulating invisible access paths faster than remediation can remove them.

For practitioners

• Inventory machine identities by owner and purpose Build a current register of service accounts, API keys, tokens, and certificates, and require each one to have a named owner, a valid purpose, and a retirement date. Prioritise identities with no active business sponsor or no recent use.
• Replace shared secrets where workloads permit it Reduce dependence on reusable credentials by moving toward secretless or strongly scoped authentication for workloads that can support it. For identities that still require secrets, constrain scope to the minimum dependency set and prevent cross-environment reuse.
• Rotate and revoke through lifecycle events Tie rotation and revocation to deployment changes, vendor offboarding, application retirement, and incident response rather than calendar-only cycles. That is the point at which stale credentials are most likely to persist unnoticed.
• Audit where secrets are created and copied Look for high-risk creation paths such as support tickets, configuration files, chat tools, and ad hoc scripts, then remove the ability to place credentials in those channels. The goal is to stop secret sprawl at the point of creation.

Key takeaways

• Machine identities are now a major governance surface, not a side effect of infrastructure automation.
• Static secrets and dormant credentials create persistent exposure because their lifecycle often outlasts the business process that created them.
• The control that matters most is lifecycle ownership, because scope, rotation, and retirement all depend on knowing who is accountable for each identity.

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.
• Static Secret: A secret — such as an API key or password — that does not change automatically over time. Static secrets require manual or scheduled rotation and represent a higher security risk than dynamic secrets or managed identities.
• Dormant Identity: A non-human identity that is no longer actively used but still has valid access. Dormancy is risky because it looks harmless while preserving credentials, permissions, and trust relationships that can still be abused or accidentally triggered.
• Identity Blast Radius: The amount of damage a compromised identity can cause across systems, data, and infrastructure. In NHI environments, it is shaped by permissions, network reach, and administrative capability rather than by the credential alone. Reducing blast radius is a containment strategy that limits lateral movement and data exposure.

What's in the full article

Saviynt's full blog covers the operational detail this post intentionally leaves for the source:

• Examples of where machine identities are being created by developers, business users, and automation workflows.
• Specific guidance on when to prefer secretless authentication versus managed secrets for workloads.
• The article's recommended hygiene steps for finding dormant machine identities across cloud, SaaS, and business applications.
• Why the vendor frames secret vaulting and secret rotation as part of PAM rather than a standalone fix.

👉 Saviynt's full post covers the lifecycle controls, secrets risks, and remediation steps in more detail.

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.