Machine identities are the new insiders in enterprise governance

At a glance

What this is: SafePaaS argues that machine identities have become the de facto insiders of modern enterprise environments because they now hold large shares of cloud privilege while remaining poorly governed.

Why it matters: IAM, IGA, PAM, and cloud security teams need to treat service accounts, APIs, bots, and certificates as governed identities because the same privilege and lifecycle controls used for people no longer cover the real access estate.

By the numbers:

• More than 70% of cloud privileges are assigned to non-human entities such as service accounts, bots, and APIs, according to SafePaaS citing Cloud Security Alliance and EM360Tech research.
• Machine identities outnumber humans by tens of thousands to one in some cloud environments, according to SafePaaS citing Cloud Security Alliance and EM360Tech research.
• The 2025 CyberArk State of Machine Identity Security Report found that machine identities outnumber human users in most enterprises and 77% represent potential compromise points, according to SafePaaS.

Context

Machine identity governance is the discipline of controlling access for service accounts, bots, APIs, containers, and certificates with the same seriousness long reserved for human users. The problem is that modern enterprises have expanded faster than their identity governance models, so large parts of the machine access estate sit outside formal ownership, review, and offboarding.

The article’s core point is that machine identities are no longer support infrastructure hidden behind applications. They are active access subjects with legitimate credentials, privileged actions, and a growing share of enterprise trust, which means the governance gap is now an access-control problem as much as an operational one.

That gap matters because automated systems do not wait for periodic certification cycles, and they often accumulate access through scripts, pipelines, and integrations that no one revalidates after the initial deployment. In many enterprises, the starting condition is already atypical: machine access exists in bulk, but governance is still organised as if people were the only meaningful identity type.

Key questions

Q: What breaks when machine identities are not included in governance reviews?

A: Human-style reviews miss the identities that actually run automation, so orphaned service accounts, overprivileged APIs, and stale certificates remain active outside ownership and expiry controls. The result is not just weak visibility. It is a control gap where the largest access population can keep operating without recertification or clear accountability.

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

A: Machine identities are often numerous, long-lived, and embedded in code or infrastructure. They are harder to review manually, easier to overlook during offboarding, and more likely to carry excessive privilege. That combination increases blast radius when a secret or token is exposed.

Q: What are the signs that service account governance is failing in an organisation?

A: Common warning signs include accounts with no clear owner, broad permissions that exceed job need, credentials stored in insecure places such as code or configuration, and service accounts that survive staff departures without reassignment. Another sign is the inability to answer who uses the account, when it was last reviewed, or whether its access still matches the application it supports.

Q: Should organisations treat machine identities differently from human accounts?

A: Yes, because the governance model is different even when the control objective is the same. Human accounts follow employment and authentication patterns; machine identities follow workload, integration, and secret-lifecycle patterns. Treating them identically leads to missed ownership, poor expiry discipline, and privilege that survives long after the business need has changed.

Technical breakdown

Why machine identities become insiders in trusted systems

A machine identity is any non-human credentialed actor that can authenticate and act inside an environment, including service accounts, bots, APIs, and certificates. The insider risk comes from legitimacy, not stealth: these identities are expected to be there, often have business-critical access, and frequently bypass the tighter scrutiny applied to human users. When they are overprivileged or unmanaged, they can move laterally, trigger workflows, and access data without looking anomalous in the way an external attacker would. That makes the trust boundary itself the problem, because the system assumes the actor is already approved.

Practical implication: govern machine identities as trusted insiders with lifecycle and privilege controls, not as incidental technical artifacts.

Why human-first IAM models miss machine lifecycle drift

Traditional IAM assumes joiner-mover-leaver patterns, periodic access reviews, and role assignment around people. Machine identities break that model because they are created by code, may be short-lived or orphaned, and often never enter the same certification workflow as employees or contractors. The result is privilege drift: credentials outlive their purpose, permissions accumulate across environments, and nobody can reliably answer who owns the identity, what it can access, or why it still exists. This is a governance failure, not merely an inventory problem.

Practical implication: extend lifecycle ownership, recertification, and offboarding logic to machine identities with the same rigor used for human access.

Why overprivileged credentials create silent breach paths

Overprivileged API keys, hardcoded passwords, and unmanaged service accounts create a low-friction path for misuse because they often authenticate directly into production systems. Once exposed or misconfigured, these credentials can be used to exfiltrate data, create backdoors, or escalate privileges without tripping the controls built for interactive users. In NHI terms, the weakness is not just secret exposure. It is the combination of standing privilege, poor ownership, and broad access scope that turns a routine automation artifact into a breach enabler.

Practical implication: tie secret inventory to permission scope so exposure and privilege are assessed together, not as separate problems.

Threat narrative

Attacker objective: The attacker aims to convert legitimate machine access into durable insider-style reach that enables theft, persistence, or sabotage without drawing human-user suspicion.

1. Entry begins when a compromised or unmanaged machine credential, such as an API key or service account, is used as a legitimate access path into a trusted enterprise system.
2. Privilege escalation follows when that identity carries broader access than its business function requires, allowing the actor to touch multiple systems or data stores.
3. Impact occurs when the credential is used to exfiltrate data, create persistent backdoors, or silently manipulate business workflows from inside the trust boundary.

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.
• Cisco Active Directory credentials leak 2025: Kraken leaked Cisco Active Directory hashes, including service and krbtgt accounts; Cisco says they came from its 2022 breach, not a new one.

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 insider-risk governance: when service accounts, bots, APIs, and certificates hold the majority of cloud privilege, the distinction between user governance and machine governance stops being useful. The governance question shifts from who logged in to what credentialed actor can already act inside the environment. Practitioners should treat machine identity as a first-class access subject, not a by-product of application delivery.

Human-centric IAM assumptions fail at machine scale: joiner-mover-leaver workflows presume a visible person, a stable employment relationship, and an access review cadence that matches human activity. Machine identities violate all three assumptions because they can be created by automation, reused across systems, and left active after the workload changes. The implication is that lifecycle governance must be designed around the identity’s functional purpose, not around human employment analogies.

Privilege drift is the real control failure, not just poor inventory: unmanaged machine identities become dangerous when ownership, scope, and expiry are all ambiguous at once. That is why manual reviews and spreadsheet governance collapse under cloud-native and DevOps conditions. The practical conclusion is that identity programmes need continuous ownership, scope, and expiration enforcement for every non-human actor.

Ephemeral credential trust debt: machine identities often look temporary, but the privileges they accumulate are persistent. That creates a governance debt where yesterday’s automation still authorises today’s access long after the original business need has changed. Practitioners should measure not only how many machine identities exist, but how many remain authorised after their purpose has ended.

Zero trust is incomplete without machine identity control: if every transaction is authenticated but the non-human actors behind those transactions are unmanaged, then trust is only being applied at the network edge. The article is right to frame machine identities as insiders, because zero trust without machine identity lifecycle, privilege, and audit control leaves the largest access population outside the model. Practitioners should align zero-trust policy with machine identity governance, not just with human login controls.

From our research library:

• 80% of identity breaches involved compromised non-human identities such as service accounts and API keys, according to the Ultimate Guide to NHIs.
• Read next: Service Account Security Guide

What this signals

Machine identity governance is becoming the control plane for modern access: when service accounts, APIs, and bots carry most cloud privilege, the practical boundary of IAM shifts from human login management to continuous control over non-human actors. Teams that still centre certification and offboarding only on employees will keep missing the identities that actually execute business processes.

Ephemeral credential trust debt: the risk is not only that machine identities exist, but that their access often outlives the workload that justified it. That creates a hidden backlog of authorised access that no human-centric review cycle will ever fully clear unless lifecycle ownership is tied to creation, usage, and expiry.

The governance response needs to be continuous rather than periodic because machine identities can be created, over-privileged, and abandoned faster than manual oversight can react. For IAM and PAM teams, the key question is no longer whether machines need control, but whether current processes can prove who owns them and when their access should end.

For practitioners

• Map every machine identity to an owner and purpose Build a complete inventory of service accounts, bots, APIs, containers, and certificates, then assign business ownership and expiration criteria so no non-human identity exists without accountability.
• Tie access reviews to machine identity lifecycle Include non-human identities in certification and recertification cycles, and require review of who owns the credential, what it can access, and whether the workload still needs it.
• Reduce standing privilege for automated actors Re-scope machine credentials to the minimum function they actually perform, especially where bots and integrations have accumulated permissions across multiple environments.
• Eliminate hardcoded and orphaned machine secrets Search code, pipelines, and application configuration for static passwords, API keys, and service account credentials that survive beyond the workload that created them.
• Log and attest machine actions continuously Require every privilege change and high-risk machine action to be logged and linked back to a business function so auditors can verify both control and accountability.

Key takeaways

• Machine identities are now operating as insiders in enterprise systems, which makes them a governance problem rather than an operations footnote.
• The article points to scale and opacity as the core issue, with cloud privileges concentrated heavily in non-human entities and many environments still managed manually.
• The practical response is to bring machine identities into the same ownership, review, and expiry discipline that already exists for human access.

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.
• Privilege Drift: Privilege drift is the gradual gap between the permissions an identity was meant to have and the permissions it actually retains. In AI agent environments, drift grows quickly because roles are reused, tasks change, and lifecycle reviews often lag behind deployment velocity.
• Orphaned Account: An orphaned account is an identity that remains active without a clear owner or business purpose. These accounts are dangerous because they often escape review, retain unnecessary access, and provide attackers with low-friction entry points into otherwise governed environments.
• 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.