Enterprise IT has changed shape over the past decade. For years, security teams focused on one main job: protecting the corporate network and managing employee passwords stored in on-premises directories. That model made sense when people were the main entities logging in. It no longer matches how systems work.
Modern companies run on software that talks to other software. Applications query databases on their own. Build tools push code to production without anyone clicking a button. Cloud platforms add and remove servers automatically as traffic rises and falls. Each of these actions needs permission to run, reach data, and cross network boundaries. None of them involves a person typing a password.
The result is a lopsided count. Software programs, scripts, and automated services asking for access now far outnumber humans on the payroll. Research from CyberArk’s 2025 Identity Security Landscape, based on a survey of 2,600 security decision-makers, found that machine identities outnumber human ones by more than 82 to 1 in the average organization. In cloud-native environments, the gap runs wider. Entro Labs put the ratio at 144 to 1 in the first half of 2025, up from 92 to 1 a year earlier, and reported that the count of non-human identities grew 44 percent in a single year. Some banks, hospitals, and technology firms report ratios closer to 500 to 1.
Securing this world means looking past employee logins. It means managing the quiet, automated accounts that keep the business running, because that is where most identity risk now lives.
What Is a Non-Human Identity?
A non-human identity is a digital credential, account, or set of permissions given to a piece of software instead of a person. It lets an application, workload, or system prove who it is, open a secure connection, and carry out approved tasks inside an IT environment.
Software needs these identities to keep working without a person standing by. A database connector, for example, uses stored credentials to pull records for a web app around the clock. If a human had to approve each request, the app would stall.
Non-human systems authenticate with credentials supplied in code, not with the tools people use. Instead of a fingerprint, a password prompt, or a code from an authenticator app, software proves itself with private keys, digital certificates, OAuth tokens, API keys, or encrypted secrets loaded into memory as the program runs.
These credentials sit everywhere. Cloud platforms such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform create them. So do internal build pipelines, configuration tools, container systems, customer platforms, and outside SaaS apps the business connects to.
Human Identities vs. Machine Identities vs. Non-Human Identities
Telling identity types apart matters, because each one behaves differently and needs different controls. One note on wording first: some vendors use machine identity and non-human identity to mean the same thing. Others treat machine identities as one specific part of a larger non-human group. Knowing that these terms overlap will save confusion when reading reports from different security sources.
Human Identities
Human identities belong to real people who use company systems through a screen.
- Employees: Staff who open business email, HR portals, file systems, and office apps.
- Contractors: Outside workers who need limited or short-term access to certain tools or environments.
- Customers: People who log into consumer apps, banking sites, or online stores.
These accounts follow a person’s lifecycle. Someone is hired, changes roles, or leaves, and access changes with them. Passwords and multi-factor prompts do most of the security work.
Machine Identities
Machine identities secure hardware, network gear, and the trust between physical or virtual devices.
- Certificates: X.509 certificates that set up encrypted TLS sessions between servers and browsers.
- Cryptographic identities: Key pairs that build trust between servers, storage systems, and network devices.
- Device identities: Unique IDs and hardware signatures tied to laptops, phones, and servers.
Their main job is to confirm that a device is real, encrypt traffic, and check that hardware has not been tampered with.
Non-Human Identities
Non-human identities cover the full range of software actors, automated workflows, and digital execution contexts.
- Service accounts: System accounts that run background processes, daemons, and database services.
- Workloads: Code running inside containers, virtual machines, or serverless functions.
- Applications: Third-party software that trades data with internal databases over background connections.
- Bots: Scripts that handle repeat jobs like backups or log archiving.
- APIs: Endpoints that use keys to pass instructions between services.
- Automation: Scripts and deployment workflows that change infrastructure and push releases.
- AI agents: Software that reviews data, calls outside services, and makes decisions on its own.
Where machine identities protect hardware and physical or virtual wires, non-human identities protect the software, workflows, and business logic running on top.
The Different Types of Non-Human Identities
Different platforms use different kinds of non-human identity. Knowing why each one exists helps teams put the right guardrails in the right places.
Service Accounts
Service accounts are non-person accounts made inside operating systems, directories, or platforms to run a specific app or background job. They let long-running processes reach file paths, directories, and network shares without tying that access to any one employee’s login.
Application Identities
An application identity stands in for a single software package inside an identity platform. Cloud services use it to control what data an app can touch when its code runs, keeping the app’s access separate from the credentials of the developer who built it.
API Keys and Tokens
API keys and tokens are strings of text that an app sends in its request headers to prove who it is. They let separate systems talk to each other, so a web app can reach a payment gateway, a mapping service, or a messaging tool.
Kubernetes Service Accounts
These give a distinct identity to processes running inside containers. They let code in a pod call the Kubernetes API, read ConfigMaps, pull secrets, and reach restricted cluster services.
Cloud Workload Identities
These let cloud resources like virtual machines, pods, and serverless functions borrow short-term permissions straight from the cloud provider. That removes the risky habit of hardcoding long-term keys into config files.
Secrets and Certificates
This group covers database passwords, SSH keys, and certificates that back-end systems use to prove trust to each other. They guard the connections between services so data only flows between verified endpoints.
CI/CD Pipeline Identities
These let build tools such as GitHub Actions, GitLab CI, and Jenkins run deployment code. They often carry heavy permissions, since they pull source code, build artifacts, and change production settings on their own.
Robotic Process Automation (RPA) Bots
RPA bots copy the way a person clicks through an app to run repetitive business tasks. They operate software, pull data from forms, and update older databases that have no modern API.
AI Agents and Autonomous Applications
AI agents are a newer class that can plan and act across several steps. They read a request, decide which services or databases to call, reach those services, and run tasks on their own. Their fast spread is a major reason non-human identities are climbing so quickly.
Why Non-Human Identities Are Growing So Quickly
The rise of non-human identities comes from the way modern software is built, with a focus on speed, scale, and small independent parts.
Cloud computing broke the link between software and fixed hardware. When companies moved off physical servers and onto on-demand cloud platforms, static setups gave way to resources that scale up and down with traffic. Every new cloud instance needs its own credentials to connect safely.
Splitting big apps into microservices multiplied the count further. A single program that once reached one database is now dozens or hundreds of small services, and each one needs its own keys to talk to the others.
Containers and orchestration tools like Kubernetes made things faster still. Containers start, do a job, and shut down in minutes or seconds. That pace demands systems that can hand out and pull back thousands of short-lived credentials every hour.
DevOps and Infrastructure as Code replaced manual steps with automated pipelines. Deployment tools need real permissions to set up servers, change security groups, edit routing, and push code to production with no one watching.
The spread of SaaS platforms, integration tools, and AI automation stretched the perimeter wider. Business runs on constant data flows between cloud apps, customer records, finance tools, and analytics, and each link needs an API key or OAuth token.
The scale shows up in the data. GitGuardian’s State of Secrets Sprawl 2026 report found that public GitHub commits rose 43 percent year over year in 2025, driven in part by AI-assisted coding. More code means more services, and more services mean more credentials in circulation.
Where Non-Human Identities Create Security Risks
Non-human identities keep modern software running, but they open real holes when no one manages them well.
Excessive Permissions
Teams often hand new accounts broad admin rights during development to avoid errors. Those rights rarely get trimmed before the app ships, so it runs in production with far more access than it needs. CyberArk found that 42 percent of machine identities already hold privileged or sensitive access.
Forgotten Service Accounts
Accounts get made for a test project, a migration, or a short vendor job. When the work ends, the account often stays active, running quietly with no one watching it.
Shared Credentials
Teams sometimes share one API key or service-account password to make setup easier. That wipes out the audit trail, so no one can trace an action back to a single service when they review the logs.
Long-Lived Secrets
Many companies create credentials that never expire. Static passwords and keys that are never rotated give an attacker unlimited time to use them if they leak. GitGuardian found that about 64 percent of secrets confirmed valid in 2022 were still active four years later.
Orphaned Identities
These appear when the person or team that made an identity leaves or moves on. With no record of who owns it, security teams are afraid to touch the account in case turning it off breaks something in production.
Lack of Ownership
Many service accounts have no listed owner at all. With no owner, no one gets rotation alerts, reviews the permissions, or checks whether the app still needs access.
Credential Exposure
Developers accidentally commit keys, private keys, and passwords into public code, plain-text config files, container images, and logs. Automated bots scan public repositories nonstop and grab exposed credentials within seconds. GitGuardian detected 28.65 million new hardcoded secrets in public GitHub during 2025 alone, a 34 percent jump over the year before and the largest single-year rise it has recorded.
Identity Sprawl
As cloud instances, SaaS links, and pipelines spread across departments, security teams lose count of how many identities exist. The ones no one tracks become blind spots that skip past security policy entirely.
How Non-Human Identities Become an Attack Path
Attackers go after non-human identities on purpose. These accounts rarely use multi-factor checks, often hold high permissions, and seldom trigger an alert when used from a strange location.
A common attack starts when a developer pushes a file with a hardcoded cloud key into a public repository. Scanning scripts spot it almost at once. The attacker uses the key to log straight into the cloud account, skipping single sign-on and multi-factor prompts.
Inside, the attacker looks for other identities with more access. If the first key can read storage buckets or build-server configs, the attacker pulls environment files that hold stronger admin tokens.
With those tokens, the attacker escalates. They abuse weak identity rules to take on admin roles, attach high-power policies to their session, or create fresh admin accounts to keep a way back in.
Then comes lateral movement. Using strong non-human credentials, the attacker moves between container clusters, production databases, and deployment services. Because these accounts run background jobs all day, the bad activity blends into normal traffic and often slips past monitoring.
This is not just theory. In March 2025, attackers compromised the widely used tj-actions GitHub Action with a stolen access token. They slipped in code that quietly pulled secrets from the build logs of more than 23,000 repositories, a clear example of how one exposed credential can spread across thousands of systems.
Managing the Lifecycle of Non-Human Identities
Securing these identities means controlling them from the moment they are made until the day they are retired.
Before stepping through the core lifecycle phases, it helps to understand that identity management is an ongoing loop rather than a one-time setup.
- Discovery: It starts with finding every identity across the whole environment. Automated scanners should sweep code repositories, cloud platforms, container registries, pipelines, and directories to build one full inventory of active credentials.
- Creation: New identities should follow set, policy-driven steps. Instead of letting developers make static keys by hand, teams should use systems that issue credentials with tight access limits and clear expiry dates built in.
- Ownership: Every identity needs a named person or team on record. That tag keeps responsibility for monitoring, approving changes, and handling retirement with a team that is still active.
- Permission Assignment: Access should match the exact task. Teams should skip default admin templates and use fine-grained rules that limit actions to specific resources, network ranges, and operations.
- Credential Rotation: Companies should drop static passwords for automated rotation. Swapping long-lived secrets for short-lived tokens shrinks the window an attacker has to use a stolen credential.
- Review: Teams should run regular access reviews, checking real activity against granted permissions. Spotting unused rights lets them trim excess access and fix drift before it turns into a weak point.
- Retirement: When a service is shut down, or a project ends, its identities must be removed right away. Automated deprovisioning makes sure unused credentials are revoked across every connected platform.
Building Visibility Across Every Non-Human Identity
You cannot secure what you cannot see. Companies need steady monitoring to track every non-human actor across on-premise and cloud systems.
Continuous discovery should run all the time, catching new credentials, exposed secrets, and unmanaged accounts the moment they show up in a repository or cloud account.
A central inventory gives one source of truth for active accounts. It should pull data from cloud providers, pipelines, container platforms, and secret vaults into a single view.
Clear ownership keeps that view useful. Linking each identity to a verified app, workload, or team removes unmanaged accounts and speeds up response when something looks wrong.
Watching real-time usage lets teams learn what normal looks like. Once they know the usual query volume, run times, and IP ranges for an account, monitoring can flag odd behavior fast.
Tracking privileged identities keeps the riskiest accounts in view. Any account with admin or sensitive access should get extra logging, tighter rotation, and instant alerts when it breaks policy.
Applying Least Privilege to Non-Human Identities
Least privilege means each identity holds only the permissions its job requires, which limits how far an attacker can move after a breach.
Role-based access control grants rights by role instead of by account. Setting clear roles for web servers, database connectors, and deployment runners keeps access consistent across similar workloads.
Short-lived credentials remove the danger of static keys. Cloud identity platforms hand out temporary tokens that expire in minutes or hours, so a stolen token is soon useless.
Just-in-time access grants extra rights only when a workflow asks for them and pulls them back once the task is done. This keeps pipelines and build servers from holding admin rights while idle.
Automated permission reviews compare granted rights against real usage from the logs. Unused rights can be pruned on their own, shrinking the attack surface without breaking live work.
Identity segmentation walls off what each identity can reach. Limiting an account to certain network segments, resource groups, or environments stops a compromised staging credential from touching production data.
How Non-Human Identity Security Fits into Enterprise Identity Programs
Non-human identity security does not replace existing security work. It adds to and connects with the access controls already in place.
Identity and Access Management platforms hold the core policy layer for managing users. Adding non-human identities extends that governance, logging, and directory sync to software accounts across every environment.
Privileged Access Management tools were once focused on admin credentials for human IT staff. Extending them to non-human accounts brings credential vaulting, secure session brokering, and tight access controls to high-risk accounts.
Secrets management platforms store, rotate, and inject sensitive keys, tokens, and passwords into running software. This ends the risky habit of hardcoding credentials into source code.
Public Key Infrastructure handles issuing, sharing, and revoking certificates. Aligning non-human identity work with PKI keeps automated mutual TLS across container clusters running safely.
Cloud Infrastructure Entitlement Management tools map complex multi-cloud permissions. They flag over-privileged accounts, review inherited roles, and spot risky permission chains.
Identity Threat Detection and Response watches credential traffic for signs of compromise. Adding non-human accounts lets it alert when a service account acts oddly, like reaching an unexpected cloud region or making abnormal API calls.
Zero Trust requires every request to be checked before access is granted. Non-human identity security supports it by removing built-in trust from automated software.
The stakes show up in the data. CyberArk’s 2025 State of Machine Identity Security Report, a survey of 1,200 security leaders, found that 50 percent of organizations had a breach tied to a compromised machine identity in the past year. Gartner projects that by 2028, one in four enterprise breaches will involve the misuse of AI agents.
Who Is Responsible for Securing Non-Human Identities?
Securing these identities takes teamwork across several groups.
- Identity and Access Management Teams: Set company-wide identity policy, run central access systems, and define governance for human and non-human accounts alike.
- Cloud Security Teams: Watch cloud service-account settings, manage permissions across clouds, and find misconfigured access.
- Platform Engineering Teams: Build secure identity creation, secret vaulting, and short-lived token tools into internal platforms.
- DevOps Teams: Handle credentials safely inside build pipelines, container scripts, and infrastructure code.
- Security Operations Centers: Watch live usage logs, investigate odd account behavior, and respond to credential alerts.
- Application Owners: Keep app documentation current, assign ownership, and review access for the apps they run.
- Governance, Risk, and Compliance Teams: Audit access controls, check alignment with regulations, and confirm that credential management meets policy.
Why Non-Human Identities Are Becoming the Largest Identity Group
The balance of identity has shifted for good. As companies add automation, cloud-native design, and integrations, non-human identities grow far faster than staff.
Cloud-native development leans on microservices and container tools that create and destroy identities on the fly. A single app that once needed a few service accounts now spins up thousands of short-lived contexts a day.
Business automation and low-code tools keep spreading across departments. Non-technical teams build workflows that link cloud apps with API keys and tokens, adding more unmanaged credentials to the pile.
The rush to deploy AI agents speeds this up further. As companies send agents to query data lakes, call internal services, and run tasks on their own, each agent needs its own secure identity.
The numbers make the trend hard to ignore. With ratios running from 82 to 1 up past 144 to 1, non-human identities already outnumber people by a wide margin in most enterprises, and Entro Labs recorded 44 percent growth in a single year. Human-centered controls alone can no longer protect these systems. Strong discovery, strict least privilege, automated rotation, and constant threat detection across the full non-human identity lifecycle are now core to keeping enterprise cloud environments safe.
