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Non-human identity (NHI) security is attracting cybersecurity vendors because applications, cloud workloads, APIs, automated pipelines, SaaS integrations and AI agents increasingly authenticate to one another without a person logging in. The risk is not simply the number of machine credentials: it is that organizations may not know what exists, who owns it, what it can access or how to disable it safely.
The market is growing, but “NHI management” is not one standardized product category. It overlaps with secrets management, cloud IAM, privileged access management (PAM), certificate tools, workload identity and application security. Buyers should compare what a product actually discovers, governs, detects and can remediate—not just its use of the NHI label.
What counts as a non-human identity?
A non-human identity is a digital identity used by a workload, application, service, script, device, integration, bot or AI agent to authenticate or obtain authorization. It may be represented by an account, a credential, a cryptographic certificate, a role, a delegated grant or a machine-to-machine trust relationship; not every NHI is an account.
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Human IAM typically asks which person can access which resource. NHI management must also answer: which workload, integration or agent can act, on whose authority, against which resources, with what permissions, and for how long?
Why the problem is expanding
Modern systems create machine-to-machine access by design. Cloud-native applications call services and databases; CI/CD pipelines deploy code; SaaS products exchange data through OAuth integrations; IoT and industrial devices communicate without human intervention. Hybrid and multi-cloud deployments spread these relationships across platforms, while short-lived workloads make ownership and inventory harder to maintain.
Development teams can create credentials faster than a centralized security team can review them. An identity may be created for a project, then remain active after the project, employee or vendor relationship ends. AI agents add another layer: they can call tools, use delegated authority and take actions at machine speed. Their effective access depends not just on a credential, but also on the agent’s permissions, task, context and runtime behavior.
Where NHI programs commonly fail
The lifecycle provides a practical way to understand the exposure. A credential can be discovered, assigned an owner and purpose, limited to necessary permissions, monitored, rotated and ultimately revoked. Risk accumulates when one or more of those steps is missing.
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- Discovery: Service accounts, shadow OAuth applications, orphaned API keys and secrets outside approved vaults can escape inventory. Duplicate identities and unclear relationships between credentials, applications, vendors and resources make the map incomplete.
- Ownership and governance: An identity without a named owner, business purpose, expiration date, approval path or documented dependencies is difficult to review or retire. This is often as much an accountability problem as a technical one.
- Excessive privilege: Broad cloud roles, production access from development pipelines, reused credentials and tokens that reach more resources than a workload needs all increase the potential impact of compromise.
- Weak monitoring: Teams may lack an audit trail for machine-to-machine behavior, visibility into third-party OAuth access or alerts for unusual token use. It can be hard to connect an automated action to the originating workload, person or vendor.
- Slow or unsafe response: Security teams may delay revocation because they do not know what depends on a credential. Conversely, rotating a credential without mapping its consumers can break production. Without a tested shutdown and recovery process, both inaction and rushed remediation carry costs.
A 2024 Dark Reading report described concerns including incomplete inventories, inactive identities, missing ownership, excessive permissions, weak monitoring and inadequate rotation or revocation. Those problems explain the market opportunity better than a headline count of machine identities: risk depends on privilege, exposure, reachability, lifetime, ownership, usage and the sensitivity of accessible resources.
What breach examples do—and do not—show
Reported incidents illustrate why credentials and machine-to-machine authorization matter, but they do not prove that a dedicated NHI platform would have prevented a particular breach.
The 2024 Dark Reading article connected the discussion to reports that attackers used exposed credentials to access a Schneider Electric Jira server and then abused an API-based authentication component; Midnight Blizzard’s access to a legacy test OAuth application with elevated privileges; compromised credentials in breaches associated with Snowflake customers; malicious OAuth applications used in GitHub extortion campaigns; and theft of secrets and authentication tokens from Hugging Face. These cases involve different systems and attack paths. The common lesson is that credentials, grants and service access need ownership, appropriate scope, monitoring and a usable revocation path—not that every incident was solely an NHI-management failure.
Why conventional IAM and PAM leave gaps—but still matter
Workforce IAM and PAM remain foundational. They manage human authentication, directory groups, administrator privileges and sessions; mature deployments may also govern some service accounts, broker credentials or control privileged access. The gap arises when machine identities are spread across cloud accounts, SaaS tools, repositories, vaults, endpoints and third-party integrations, or are created outside central identity workflows.
Tokens and keys may not appear as ordinary directory objects. A workload may be ephemeral, an OAuth grant may belong to an integration, and a credential may be associated with an application or departed employee rather than a current accountable owner. A platform that covers one system will not necessarily reveal identity relationships across all of them.
The direction is convergence, not replacement: identity-security vendors are extending human IAM and PAM programs toward machine identities, while specialist products focus on discovery, governance, secrets exposure or workload access. CyberArk’s machine-identity offering, for example, describes coverage for secrets, certificates, workload identities and SSH keys. That breadth does not make every NHI problem identical or eliminate the need to assess existing controls.
A fragmented vendor landscape
The following groups describe primary product emphasis, not mutually exclusive categories. Capabilities and packaging change; use vendors’ current documentation and a scoped evaluation to confirm coverage for your environment.
| Category | What it primarily addresses | Examples and fit |
|---|---|---|
| Broad machine-identity security | Secrets, certificates, workload identities and SSH keys, often alongside PAM and identity-security programs. | CyberArk is relevant to enterprises seeking broader machine-identity coverage. Its acquisition of Venafi for $1.54 billion, announced in 2024, was a high-profile signal of the strategic importance of machine identity. CyberArk now calls the former Venafi Firefly product Workload Identity Manager. |
| NHI discovery and governance | Inventory, ownership, relationships, permissions, lifecycle processes, posture and, depending on the product, detection and remediation. | Astrix describes discovery and management across service accounts, OAuth apps, API keys, IAM roles, secrets and AI-related identities. Entro describes discovery, lineage, lifecycle, secrets security and threat detection. Oasis Security describes NHI inventory, policy controls and AI-assisted risk prioritization. These products overlap, but buyers should validate the particular identity types and actions covered. |
| Secret exposure management | Finding credentials exposed in repositories or developer environments, and connecting those findings to remediation or identity governance. | GitGuardian grew from secrets detection and now markets NHI Governance. It is relevant when leaked credentials and code exposure are a priority, but secret scanning alone is not certificate lifecycle management, workload identity or runtime agent control. |
| Secretless workload access | Replacing persistent application secrets with short-lived, policy-based access issued or brokered when needed. | Aembit emphasizes workload identity and just-in-time credentials. CyberArk Workload Identity Manager is another workload-identity offering. This approach is most directly relevant when reducing stored, long-lived credentials is the immediate goal. |
| Adjacent controls | Specific parts of the lifecycle, often already deployed in an organization. | Cloud IAM and workload identity, Kubernetes identity, secrets managers, certificate authorities, PAM, CI/CD security, OAuth governance, cloud-security posture tools, secret scanners, SIEM and SOAR all contribute. Their coverage can be valuable but fragmented. |
The buying question is therefore not simply “Which NHI vendor is best?” It is “Which unmanaged identity population is creating the greatest risk, and which existing or new control should own it?” A tool focused on OAuth and API-key discovery may not provide certificate lifecycle management. A secretless access broker may not supply cross-environment inventory. A repository scanner may detect exposed keys but not govern an agent’s runtime actions.
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AI agents make authorization more consequential
An AI agent is not automatically a wholly new identity type; it may act through service accounts, OAuth grants, workload identities or delegated human access. What changes is the way authority is exercised. An agent can choose among tools, make decisions based on context and perform multiple actions under an identity that may have been granted for a broader purpose.
For agent use cases, distinguish six levels of capability: discovering agents; identifying their owners and provenance; governing permissions; monitoring runtime behavior; enforcing authorization at the action level; and suspending the agent or revoking its delegated access quickly. A product that inventories agents does not necessarily control what they can do once running. Ask whether it records the user or process that initiated an action, the tool call, resource, outcome and authorization used.
Also establish whether policies constrain each agent’s purpose, resources and duration, and whether third-party or shadow agents are covered. “AI-agent security” can mean anything from inventory to runtime enforcement; those are materially different controls.
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How to decide whether to buy a dedicated NHI platform
- Set scope before comparing products. List the identity populations that matter: service accounts, API keys, OAuth applications, cloud roles, certificates, SSH keys, Kubernetes and CI/CD identities, secrets in code or endpoints, third-party integrations, and AI agents or MCP servers. Do not assume one product covers them all.
- Map current controls and gaps. Identify what cloud IAM, PAM, vaults, certificate tools, AppSec, SaaS security and SIEM/SOAR already discover or govern. Look for blind spots across platforms and ownership handoffs, not just duplicated features.
- Test discovery and context. Ask which clouds, SaaS applications, repositories, vaults, endpoints, databases and orchestration systems are supported. Can the product find identities outside approved vaults, shadow grants and stale credentials? Does it show relationships and update promptly after creation, rotation or revocation?
- Demand actionable ownership data. Useful context includes creator, current owner, application or workload, vendor, environment, permissions, resources accessed, last use, creation and expiry dates, dependencies and business criticality. Without it, an inventory may become another dashboard rather than a remediation system.
- Evaluate safe lifecycle changes. Can the tool issue short-lived access, rotate or revoke credentials, right-size permissions, assign owners and decommission identities? Does it map dependencies, stage changes, notify service owners, support rollback and test impact before changes reach production?
- Verify detection and response. Separate static posture checks and leaked-secret detection from behavioral anomaly detection and runtime action monitoring. Confirm whether a real response can be triggered—such as disabling a token, blocking an OAuth app, reducing permissions or opening an ITSM/SOAR workflow—and who approves it.
- Check operational integration. Assess compatibility with current vaults, cloud IAM, PAM, CI/CD, Kubernetes, SIEM, SOAR, ITSM and developer workflows. Moving every credential into a new proprietary vault may be impractical in a heterogeneous enterprise.
- Measure outcomes, not inventory size. Track ownership coverage, privileged identities reduced, stale credentials retired, credential lifetime, rotation success, time to revoke access and time to contain a compromised integration. A high NHI count is not itself a risk score.
Trade-offs and limits to keep in view
A dedicated platform adds another control plane. It may provide cross-environment discovery and relationship context unavailable in isolated tools, but it also adds integrations, operational work and overlap among IAM, AppSec, cloud-security and DevOps teams. Organizations with relatively contained environments may first improve native inventory, ownership, vaulting, rotation, least privilege, OAuth governance and logging.
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Inventory without remediation is incomplete. Discovery creates value only if teams can assign owners and act on findings. Remediation must account for dependencies and production uptime; a stale key is risky, but an unplanned rotation can interrupt a critical service.
Short-lived credentials reduce persistence, not all risk. They can make a stolen credential less useful, but do not prevent excessive authorization, compromised workloads, malicious OAuth apps, over-permissioned agents, weak issuance policies or abuse during a credential’s valid window. Identity, authorization, runtime monitoring and logging still matter.
Counts and ratios are not universal measures. The 2024 reporting discussed estimates such as 50 NHIs per human identity and survey responses about investment plans, incidents and visibility. Such figures depend on definitions and surveyed populations; they should not be treated as universal 2026 measurements. Whether a count includes credentials, tokens, roles, workloads, certificates or integrations changes the result. Vendor claims of still higher ratios likewise need their methodology and population stated.
Why vendors are pursuing the category
The commercial case is the gap between how much machine-to-machine access organizations rely on and how unevenly they manage it. Established vendors can extend secrets, PAM, certificate and cloud-identity products; newer specialists can focus on cross-platform discovery, ownership, relationship graphs, exposure detection or agent governance. CyberArk’s Venafi acquisition and the expanded product positioning of companies such as Astrix, Entro and Oasis reflect that competition, while products such as Aembit target the different problem of issuing workload access without persistent secrets.
Funding and product announcements are market signals, not proof that a category has converged or that one platform is necessary. In 2024, Astrix announced a $45 million Series B, bringing its reported funding at that time to $85 million, according to the contemporary Dark Reading account. Such historical figures explain investor interest; they do not establish current product fit, maturity or effectiveness.
For most organizations, the sensible sequence is to identify the highest-risk unmanaged identity population, establish ownership and least privilege, and make rotation and revocation workable. Buy a dedicated NHI platform when fragmentation across clouds, SaaS, repositories and business units prevents existing controls from providing the required discovery, context or response. The value should be demonstrable in reduced privilege, shorter credential life, clearer accountability and faster containment—not in adopting a label.
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