Machine identity governance is a missing layer in zero trust strategy

At a glance

What this is: This is an analysis of why machine identities and their secrets have become a core zero trust governance problem as cloud, SaaS, and DevOps expand the number of non-human access paths.

Why it matters: IAM and NHI teams need to treat machine identity lifecycle, secret rotation, and monitoring as part of zero trust if they want reliable least privilege and better blast-radius control.

By the numbers:

• 45:1.
• The CyberArk 2023 Identity Security Threat Landscape report finds that organisations expect an increase of 68% in the number of SaaS applications deployed in their environment.
• Another CyberArk report indicates that 80% of organisations will use three or more cloud service providers.
• The CyberArk article says 65% of organisations either took steps to protect machine identities last year or plan to do so in the next 12 months.

👉 Read CyberArk's analysis of machine identities in zero trust strategy

Context

Machine identity governance is the discipline of controlling how software, workloads, and devices authenticate and obtain access. In a zero trust model, those identities cannot be treated as a side issue because they often carry service-level privileges, embedded secrets, and automated access paths that humans never see. As cloud services, remote work, and mobile access erode the old perimeter, the operational gap is no longer whether machines need trust controls, but whether IAM teams can apply them consistently.

CyberArk frames the problem as one of scale, speed, and visibility. Machine identities proliferate faster than manual inventories can track, and the supporting secrets often live in CI/CD pipelines, cloud services, or application configs where lifecycle controls are inconsistent. That starting position is common in modern hybrid estates, which is why machine identity governance now needs to sit inside zero trust policy, not beside it.

Key questions

Q: How should security teams govern machine identities in zero trust environments?

A: Security teams should govern machine identities with the same discipline used for privileged human access: inventory, ownership, policy-based approval, rotation, monitoring, and revocation. Zero trust only works when every non-human credential has a known purpose and a short, enforceable lifecycle. Without that, machine access becomes a hidden standing privilege layer inside the environment.

Q: Why do machine identities create more risk than human accounts in many environments?

A: Machine identities often create more risk because they are more numerous, run continuously, and are frequently granted broad access to keep systems working. They also rely on secrets that can be copied into code, pipelines, or configs, which makes exposure harder to detect. The risk grows when teams cannot see where those credentials are used.

Q: What is the difference between secrets rotation and secrets governance?

A: Secrets rotation changes the credential on a schedule or after an event, while secrets governance defines who owns the secret, where it is used, when it expires, and how it is revoked. Rotation is only one control. Governance is the broader lifecycle model that keeps rotation from becoming a box-ticking exercise.

Q: When should organisations treat a machine identity like privileged access?

A: Organisations should treat a machine identity like privileged access whenever it can reach production systems, sensitive data, cloud control planes, or other identities. High reach plus weak visibility creates the same blast-radius concerns that PAM is meant to reduce. If the workload can alter infrastructure or exfiltrate data, it needs privileged scrutiny.

Technical breakdown

How machine identities expand the zero trust attack surface

A machine identity is a non-human credentialed entity, such as a service account, workload, certificate, API key, or automation token, that authenticates to other systems. In practice, these identities often outnumber human accounts and operate continuously, which creates a much larger and more persistent access surface. Zero trust assumes every request must be verified, but machine identities are frequently trusted by default once provisioned. That mismatch becomes dangerous when credentials are long-lived, embedded in code, or reused across environments. The main architectural failure is not the identity itself, but the absence of lifecycle discipline around issuance, rotation, and revocation.

Practical implication: Treat each machine identity as a governed access path with a defined owner, expiry, and revocation process.

Secrets rotation and renewal in dynamic cloud environments

Secrets management is the control plane for machine authentication. In hybrid and multi-cloud environments, the problem is that secrets are distributed across applications, pipelines, and platform-native services, while the environment changes faster than manual processes can keep up. Automated issuance, renewal, and revocation reduce the chance that stale secrets remain valid after a workload is decommissioned or repurposed. Rotation alone is not enough if teams cannot detect where a secret is used or whether it has been copied into multiple contexts. The key technical requirement is linkage between identity inventory, secret storage, and policy enforcement.

Practical implication: Build automation that ties secret rotation to workload inventory, so revocation follows the actual lifecycle of the identity.

Why monitoring matters for machine identity abuse

Monitoring machine identities means observing authentication patterns, secret usage, and anomalous access paths at runtime. Because these identities authenticate non-interactively, compromise often looks like normal machine behaviour until the activity reaches unusual destinations or volumes. This makes audit logs and telemetry essential for spotting hard-coded secrets, overused credentials, and unexpected cross-environment access. The security value comes from correlating identity events with workload context, not from storing logs in isolation. Without that correlation, teams can know a secret was used but still not know whether the use was legitimate, automated, or malicious.

Practical implication: Correlate machine identity telemetry with workload context so abnormal access can be detected before it spreads.

Breaches seen in the wild

• Emerald Whale breach — exposed Git config files led to 15K secrets stolen and 10K repo compromises.
• CI/CD pipeline exploitation case study — full server takeover via exposed .git directory and mismanaged CI/CD pipeline secrets.

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 now a zero trust design problem, not just an operational hygiene issue. Once non-human credentials outnumber human accounts, the governance model has to assume a much larger population of actors with varying privilege levels and weak ownership. That changes the control objective from simple authentication to continuous lifecycle governance. Practitioners should treat machine identity sprawl as a structural risk to least privilege.

Ephemeral infrastructure does not remove standing trust, it often hides it. Containers, serverless functions, and automation scripts can create the impression of short-lived access while leaving behind durable secrets, certificates, or shared service accounts. The result is trust debt: access appears temporary in the application layer but remains persistent in the identity layer. Organisations should map where ephemeral workloads still depend on durable credentials.

Zero trust fails when machine identity controls are bolted on after deployment. If identity security is not built into CI/CD, cloud provisioning, and workload onboarding, teams inherit access paths they cannot easily inspect or revoke. That is why machine identity policy must be part of the initial architecture, not an exception process. Practitioners should align deployment automation with identity lifecycle controls from day one.

Machine identity governance now sits at the intersection of IAM, PAM, and secrets management. Service accounts and workload credentials can behave like privileged access even when they are not labelled that way, especially when they can reach production systems or sensitive data. The governance model must therefore combine ownership, approval, rotation, monitoring, and revocation. Teams should stop managing these identities as isolated technical artifacts.

From our research:

• Only 1.5 out of 10 organisations are highly confident in their ability to secure NHIs, compared to nearly 1 in 4 for securing human identities, according to The State of Non-Human Identity Security.
• 85% of organisations lack full visibility into third-party vendors connected via OAuth apps, and 38% have no or low visibility, according to The State of Non-Human Identity Security.
• If machine identities are to fit zero trust, the next step is to pair lifecycle control with workload identity standards such as Guide to SPIFFE and SPIRE.

What this signals

Machine identity governance is becoming a programme-level requirement, not a niche platform task. As organisations add more SaaS, cloud providers, and automated workloads, the real constraint is whether identity teams can prove where non-human access exists and who owns it. The governance programme should move from periodic cleanup to continuous control, with inventory and review loops feeding operational change.

Ephemeral access does not equal low risk. When short-lived workloads still rely on durable secrets, the control burden shifts to revocation speed and telemetry quality. For security teams, that means hardening lifecycle controls around deployment events, decommissioning, and exception handling before the environment scales further.

For practitioners

• Define an inventory for all machine identities Create a complete register of service accounts, API keys, certificates, tokens, automation scripts, and workload identities, then assign an owner and business purpose to each entry. Use the inventory as the control baseline for review, renewal, and revocation. A machine identity without ownership should be treated as unmanaged.
• Automate secret rotation and revocation Replace manual secret handling with policy-driven rotation tied to workload lifecycle events, including deployment, decommissioning, and privilege change. Ensure that revocation removes access at the system level, not just in documentation. Secrets that cannot be rotated or traced should be prioritised for redesign.
• Integrate identity controls into CI/CD Insert machine identity issuance, approval, and renewal checks into build and release pipelines so access is created and removed with the application lifecycle. This reduces hard-coded secrets and prevents long-lived credentials from being copied into code or configuration. Pipeline gates should block releases that introduce unmanaged credentials.
• Monitor for anomalous machine authentication patterns Track unusual certificate use, excessive token reuse, authentication from unexpected workloads, and access to new cloud regions or tenants. Combine logs from identity, cloud, and workload platforms so investigations can separate legitimate automation from abuse. Alerting should be tuned to the behaviour of each workload class.

Key takeaways

• Machine identities are now large enough in number and privilege to reshape how zero trust must be implemented.
• Lifecycle failures around secrets, rotation, and revocation create hidden standing access even in modern cloud estates.
• Security teams need inventory, automation, and runtime monitoring before machine identity sprawl becomes unmanageable.

Key terms

• Machine Identity: A machine identity is the credentialed identity assigned to a non-human entity such as a service account, API client, workload, certificate, or automation script. It authenticates software and devices to other systems and often carries access that is broader, longer-lived, and less visible than human access.
• Secrets Lifecycle: Secrets lifecycle is the full management process for credentials from creation through storage, rotation, use, renewal, and revocation. In NHI programmes, lifecycle discipline matters because secrets that outlive their intended purpose become standing access, especially in cloud and CI/CD environments.
• Zero Trust: Zero trust is an architecture and operating model that assumes no entity is trusted by default, even inside the network perimeter. For machine identities, that means every non-human access request should be verified, constrained, monitored, and revoked when it is no longer needed.
• Standing Privilege: Standing privilege is access that remains continuously available rather than being granted only when needed. For machine identities, it often appears as long-lived keys, reusable tokens, or certificates that stay valid across deployments, creating a larger blast radius when compromised.

Deepen your knowledge

Machine identity governance and secrets lifecycle controls are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are building zero trust controls around non-human access, it is worth exploring.

This post draws on content published by CyberArk: Why Machine Identities Are Essential Strands in Your Zero Trust Strategy. Read the original.