Non-Human Identity: Types, Risks, and 5 Best Practices

What Is a Non-Human Identity? 

A non-human identity (NHI) is a digital identity used by software (such as applications, APIs, bots, AI agents, and cloud workloads) to automatically authenticate and access systems. Unlike human logins, NHIs operate autonomously and are verified by secrets like API keys, tokens, or cryptographic certificates.

NHIs are the invisible workforce of the digital world, routinely outnumbering human users by a ratio of 40:1 or more in modern enterprises. Because they are utilized for automation and machine-to-machine communication, they present a massive attack surface.

Common types of NHIs:

• Service accounts: System accounts used by background programs to perform automated tasks.
• API keys and tokens: Digital credentials used to let different software applications talk to each other.
• Workloads: Temporary or permanent cloud instances, containers, or virtual machines running code.
• Certificates and SSH keys: Cryptographic credentials that authenticate systems, encrypt communications, and enable secure machine-to-machine or administrative access.
• Bots and AI agents: Automated scripts or semi-autonomous tools used to retrieve information or perform workflows.

This is part of a series of articles about information security

Why Non-Human Identities Matter 

NHIs Outnumber Human Identities

In most modern enterprises, the number of non-human identities far exceeds the number of human users. Automation, cloud environments, and service integrations generate a large volume of machine identities, each representing a potential point of access. For example, a single cloud application may create dozens or hundreds of service accounts, tokens, or certificates to interact with databases, APIs, and other services.

Implications:

This growth makes tracking and managing NHIs more difficult than managing human user accounts. Organizations often lose visibility into how many NHIs exist, what they access, and who is responsible for them. As a result, many NHIs operate unchecked, increasing the risk of unmanaged or rogue identities being exploited or causing operational issues.

They Are Attractive Attack Targets

NHIs often have access to sensitive systems, data, or privileged functions, making them valuable targets for attackers. Compromising a non-human identity can provide persistent, automated access without raising suspicion, since NHIs typically operate outside regular working hours and generate routine activity. Attackers can use stolen NHIs to move laterally, escalate privileges, or exfiltrate data without triggering traditional user-based security alerts.

Implications:

NHIs are less likely to be protected by strong authentication or regularly rotated passwords. Many organizations do not apply the same security controls to non-human credentials as they do to human accounts, leaving these identities exposed for extended periods. This lack of oversight allows attackers to exploit NHIs longer, increasing the potential damage from a breach.

They Expand the Attack Surface

Every non-human identity represents an additional entry point into an organization’s digital environment. As the number of NHIs grows, so does the attack surface, making it harder to secure the ecosystem. NHIs can interact with internal resources, external partners, and cloud services, often bridging otherwise isolated systems and spreading risk across domains.

Implications:

The volume and distribution of NHIs make it difficult for security teams to monitor all interactions. Undetected vulnerabilities or misconfigurations in NHIs can create blind spots that adversaries exploit. Risk management requires identifying, monitoring, and securing every NHI within the organization.

Human Identity vs. Non-Human Identity 

Human identities are digital representations of real people, used to grant access to systems and resources based on their roles, responsibilities, and organizational context. These identities are typically managed through user accounts, with authentication mechanisms like passwords, biometrics, or multi-factor authentication (MFA). Human identities are subject to onboarding and offboarding processes, regular credential rotation, and oversight by IT or HR departments.

Non-human identities are created for technical entities, such as applications, services, or automated workflows. Their lifecycle is tied to the system or process they support. NHIs may not have regular reviews or owners, making them more susceptible to misconfiguration, overprivileging, or neglect. Effective security requires treating NHIs with the same rigor as human identities, including least privilege, monitoring, and regular audits.

Common Types of Non-Human Identities 

1. Service Accounts

Service accounts are non-human identities created for running applications, background services, or automated tasks. These accounts authenticate and authorize processes that interact with other systems or resources. Service accounts often have elevated permissions to ensure uninterrupted operation, which can make them targets if not properly managed.

Recommended actions:

Managing service accounts requires strict control over their creation, usage, and deprovisioning. Organizations should apply least privilege, regularly review access, and rotate credentials frequently. Failure to do so can result in persistent, high-risk access points that attackers exploit to move laterally or escalate privileges.

2. API Keys and Tokens

API keys and tokens grant automated access to web services, cloud APIs, and integrations. These credentials are embedded within applications or scripts to support machine-to-machine communication. API keys and tokens can be difficult to track and secure as the number of integrations grows. If exposed or leaked, API keys and tokens can be used to access sensitive data, manipulate services, or disrupt operations. 

Recommended actions:

Organizations should minimize assigned privileges, use short-lived tokens when possible, and monitor for unauthorized usage. Proper lifecycle management and secure storage reduce risk.

3. Workload Identities

Workload identities are assigned to software workloads, such as containers, virtual machines, or serverless functions, enabling them to authenticate and interact with other services. These identities support dynamic, cloud-native environments where workloads are frequently created, destroyed, or scaled in response to demand. Workload identities can become difficult to manage as environments grow more complex. Without controls, workloads may inherit excessive privileges or persist beyond their intended lifespan. 

Recommended actions:

Organizations should automate creation and deprovisioning, enforce least privilege, and integrate identity management into DevOps pipelines.

4. Certificates and SSH Keys

Certificates and SSH keys are cryptographic credentials used to authenticate systems and encrypt communications. Certificates are commonly used for securing web traffic (TLS/SSL), while SSH keys provide secure remote access to servers and devices. Mismanagement of certificates and SSH keys can lead to unauthorized access or service disruptions. Certificates may expire unnoticed, or private keys may be improperly stored. 

Recommended actions:

Organizations should implement automated discovery, inventory, and renewal processes, and enforce strict controls over key distribution and usage.

5. Bots and AI Agents

Bots and AI agents are automated software entities that perform tasks ranging from customer support to data analysis. Each bot or agent typically requires its own identity to interact with systems, access data, and perform actions on behalf of users or organizations. As their use expands, their identities must be managed like other NHIs. Bots and AI agents can introduce risks such as uncontrolled data access or unintended actions if their identities are overprivileged or not monitored. 

Recommended actions:

Organizations should establish policies for identity creation, access assignment, and activity monitoring. Regular audits and integration with security operations help ensure they operate within defined parameters.

Non-Human Identity Security Risks 

Overprivileged Access

Overprivileged access occurs when a non-human identity is granted more permissions than necessary to perform its intended function. This often results from default configurations, convenience, or unclear requirements. Overprivileged NHIs can access sensitive systems or data and, if compromised, give attackers broad capabilities to move laterally, escalate privileges, or exfiltrate information.

How to address: 

Regularly reviewing and right-sizing NHI permissions reduces risk. Organizations should enforce least privilege, ensuring that each NHI has only the access needed. Automated tools can help identify excessive permissions and adjust access rights, reducing the attack surface and impact of credential compromise.

Orphaned Identities

Orphaned identities are NHIs that remain active after the associated system, service, or process is decommissioned. These accounts can accumulate over time, especially in dynamic environments. Orphaned NHIs are not actively managed or monitored, making them attractive entry points. These identities often retain access to critical resources. 

How to address: 

Organizations should implement automated discovery and deprovisioning to identify and remove unused or obsolete NHIs. Maintaining an up-to-date inventory and clear ownership prevents orphaned identities from becoming long-term vulnerabilities.

Long-Lived Credentials

Long-lived credentials are passwords, API keys, tokens, or certificates that remain valid for extended periods without rotation or expiration. Because they are often embedded in application code, configuration files, or automation scripts, replacing them can disrupt services. Organizations frequently delay rotation, increasing the window of opportunity if credentials are exposed.

How to address: 

Organizations should replace long-lived credentials with short-lived, automatically issued credentials when possible. Where long-lived credentials are required, they should be stored in a dedicated secrets management solution, rotated regularly, and monitored for unauthorized use. Automated rotation and expiration policies reduce the impact of credential theft and limit persistent access.

Supply Chain and Third-Party Access

Many non-human identities connect with external vendors, cloud platforms, SaaS applications, and development tools. These identities enable integrations that support business operations, but they also extend trust beyond the organization’s direct control. If a third-party system is compromised, attackers may abuse these identities to access internal resources.

How to address: 

Organizations should review permissions granted to third-party NHIs and restrict access to only required resources. Regular audits, continuous monitoring, and credential rotation reduce the risk of supply chain attacks. When possible, organizations should require short-lived credentials and maintain visibility into all external identities connected to their environment.

Lack of Ownership

Many non-human identities do not have a clearly assigned owner responsible for managing their lifecycle. As teams change, projects end, or applications are replaced, ownership information can become outdated or disappear. Without accountability, NHIs are less likely to receive access reviews, credential rotation, or timely deprovisioning.

How to address: 

Every non-human identity should have a designated owner responsible for approving its creation, reviewing its permissions, and removing it when no longer needed. Maintaining ownership information as part of an NHI inventory improves visibility and accountability. It also makes it easier to identify unused identities, respond to incidents, and ensure that every NHI remains necessary and secured.

Non-Human Identity Lifecycle Management 

Here’s an overview of the process of managing the full lifecycle of NHIs.

Step 1: Discovery

The first step in managing non-human identities is discovering every identity across the environment. This includes service accounts, API keys, certificates, workload identities, SSH keys, and other machine credentials used in on-premises, cloud, and SaaS environments. Because NHIs are often created automatically by applications and infrastructure, many organizations lack a complete inventory.

Continuous discovery maintains visibility as environments change. Automated tools can identify new identities, detect unmanaged credentials, and map where NHIs are used and what resources they can access. A complete inventory provides the foundation for governance, risk assessment, and lifecycle management.

Step 2: Ownership Assignment

Every non-human identity should have a clearly defined owner responsible for its security and ongoing management. The owner is typically the application owner, service owner, or team that depends on the identity. Clear ownership ensures accountability for approving access, reviewing permissions, and retiring the identity when no longer needed.

Ownership information should be documented and kept up to date throughout the identity’s lifecycle. Organizations should regularly verify that owners are still responsible for the associated application or service. This reduces orphaned identities and improves accountability during audits and investigations.

Step 3: Access Provisioning

Once an NHI has an assigned owner, it should be granted only the permissions required to perform its intended function. Access should follow least privilege, avoiding broad or unnecessary permissions. Standardized provisioning processes help ensure consistent access controls across environments.

When possible, organizations should automate access provisioning through identity and access management systems or infrastructure-as-code workflows. Automation reduces manual errors, enforces policy, and keeps permissions consistent as applications are deployed or updated.

Step 4: Usage Monitoring

After deployment, non-human identities should be monitored to understand how they are used. Monitoring includes tracking authentication events, resource access, privilege usage, and unusual behavior that could indicate compromise or misuse. Since NHIs often perform predictable tasks, deviations from normal activity can indicate risk.

Security teams should integrate NHI activity into logging, monitoring, and threat detection platforms. Correlating identity activity with other security events improves incident detection and response to suspicious behavior involving machine identities.

Step 5: Access Review

Non-human identity permissions should be reviewed regularly to verify that they remain appropriate. As applications evolve and infrastructure changes, NHIs often accumulate unnecessary permissions. Periodic reviews help identify excessive access and reduce the attack surface.

Reviews should validate the identity’s owner, confirm that the identity is still needed, and ensure that assigned permissions align with current business requirements. Automated reporting and access analytics can simplify this process by highlighting dormant identities and excessive privileges.

Step 6: Rotation and Renewal

Credentials associated with non-human identities should be rotated or renewed on a regular schedule. Passwords, API keys, certificates, tokens, and SSH keys all have finite lifecycles and should be replaced before they become security risks or expire. Automated rotation reduces the chance of credential theft leading to long-term unauthorized access.

Organizations should adopt automated certificate renewal, secret rotation, and token issuance when possible. Short-lived credentials limit the usefulness of stolen credentials and reduce manual credential management.

Step 7: Deprovisioning

When an application, service, integration, or workload is retired, its associated non-human identities should be removed promptly. Deprovisioning includes disabling accounts, revoking credentials, deleting certificates and keys, and removing unnecessary permissions. Delayed or incomplete deprovisioning leaves unused identities available for abuse.

Organizations should integrate deprovisioning into application retirement and infrastructure management processes. Automated workflows help ensure that NHIs are removed when no longer required, reducing orphaned identities and maintaining an accurate inventory of active machine identities.

Non-Human Identity Management Best Practices 

Here are some of the ways that organizations can better manage NHIs.

1. Maintain a Complete NHI Inventory

Organizations should maintain a centralized inventory of every non-human identity across on-premises, cloud, and SaaS environments. The inventory should include details such as identity type, owner, associated application or workload, permissions, credential type, and lifecycle status. A complete inventory provides the visibility needed to manage risk and enforce security policies consistently.

The inventory should be updated continuously rather than through periodic manual reviews. Automated discovery tools can identify newly created identities, detect unmanaged credentials, and flag orphaned or inactive NHIs. Maintaining accurate records supports incident response and compliance requirements.

Key actions:

• Automatically discover non-human identities across cloud, SaaS, and on-premises environments.
• Record ownership, permissions, credential type, and associated applications.
• Identify orphaned, inactive, or duplicate identities.
• Continuously update the inventory as identities are created, modified, or retired.

2. Enforce Least Privilege

Every non-human identity should be granted only the permissions necessary to perform its intended function. Limiting access reduces the potential impact if an identity is compromised and helps prevent attackers from using excessive privileges to move laterally or access sensitive resources. Least privilege should be applied consistently across service accounts, workload identities, API credentials, and other machine identities.

Organizations should review permissions regularly to remove unnecessary access as applications and infrastructure evolve. Automated entitlement analysis can help identify overprivileged NHIs and recommend permission reductions.

Key actions:

• Grant only the minimum permissions required for each non-human identity.
• Review and remove excessive or unused permissions regularly.
• Use short-lived credentials where supported.
• Continuously monitor for privilege escalation and permission drift.

3. Monitor Runtime Behavior

Monitoring how non-human identities behave during normal operation helps detect misuse and configuration issues. Runtime monitoring should capture authentication attempts, resource access, privilege usage, API activity, and changes to identity configurations. Because many NHIs perform repetitive and predictable tasks, unusual behavior can stand out.

Continuous monitoring enables security teams to identify compromised credentials, unauthorized access attempts, or unexpected changes in application behavior. Integrating runtime telemetry into security monitoring platforms improves visibility into machine identity activity.

Key actions:

• Monitor authentication, API usage, and resource access continuously.
• Alert on unusual activity such as unexpected privilege use or new resource access.
• Correlate NHI activity with endpoint, cloud, and network telemetry.
• Baseline normal behavior and investigate significant deviations.

4. Include NHIs in SOC Investigation Workflows

Security operations centers should investigate non-human identities with the same level of attention as human user accounts. When responding to alerts, analysts should determine whether an NHI was involved, what resources it accessed, and whether its permissions contributed to the incident. Ignoring machine identities can leave attack paths undiscovered.

Investigation workflows should include identity ownership, associated applications, historical activity, and current privileges. This context helps analysts assess the scope of an incident, identify affected systems, and determine whether credentials need to be rotated or access revoked.

Key actions:

• Include non-human identities in incident triage and threat investigations.
• Enrich alerts with identity ownership, permissions, and application context.
• Rotate or revoke credentials immediately after suspected compromise.
• Update detection rules based on NHI-related attack patterns and lessons learned.

5. Use Behavior Analytics to Detect Anomalies

Behavior analytics helps establish a baseline for how non-human identities operate and identifies activity that deviates from expected patterns. Examples include accessing unfamiliar systems, authenticating from unusual locations, performing unexpected actions, or using privileges not previously exercised. These anomalies may indicate credential compromise, application misconfiguration, or malicious activity.

By combining behavior analytics with threat detection and identity context, organizations can detect attacks that rule-based monitoring might miss. Machine learning and statistical models can prioritize high-risk anomalies, allowing security teams to investigate suspicious NHI activity while reducing false positives.

Key actions:

• Build behavioral baselines for service accounts, workloads, APIs, and AI agents.
• Detect unusual authentication, privilege use, and access patterns.
• Prioritize anomalies using identity risk and asset criticality.
• Combine behavior analytics with threat intelligence and identity context to reduce false positives.

Securing Non-Human Identities with Exabeam User and Entity Behavior Analytics (UEBA)

Because non-human identities operate autonomously, generate routine activity, and often fall outside traditional user-based controls, detecting when one is misused requires understanding what normal behavior looks like for each identity. Exabeam delivers advanced UEBA that uses AI and automation to help security operations teams detect, investigate, and respond to threats involving users, entities, and AI agents. Its New-Scale Analytics engine applies risk-based anomaly detection to user and entity activity, while Agent Behavior Analytics (ABA) extends that same model to AI agents and other non-human behavior, giving teams visibility into the machine identities that dominate modern environments.

Key capabilities of Exabeam UEBA:

• Behavioral detection across non-human identities: UEBA applies behavioral analytics to detect risk in users, entities, and non-human identities, while ABA uses the same approach for AI agents and autonomous activity, closing visibility gaps as environments become more automated.
• Behavioral baselines and risk scoring: New-Scale Analytics builds behavioral baselines and uses business context to refine risk scores, surfacing subtle changes in users, entities, and non-human identities and opening a case for investigation when risk crosses a set threshold.
• Entity context with Attack Surface Insights: Attack Surface Insights identifies entities in parsed logs and connects attributes and contextual data to build profiles that strengthen behavioral detections across endpoints, servers, and applications.
• Automated investigation timelines: Automated timelines organize related detections chronologically to visualize the full scope of a threat, summarize anomalous activity, and apply prebuilt playbooks that reduce manual routines so teams respond faster.
• Flexible deployment and AI-driven investigation: New-Scale Analytics runs on top of an existing SIEM to add advanced behavioral analytics, while New-Scale Fusion serves as a full replacement, and generative AI accelerates investigations with natural-language queries, reporting, and recommended response steps.

Integrating ABA with Praxen and Observra

To secure AI agents, Exabeam combines runtime analytics with open-source frameworks for telemetry and verification. Integrating Agent Behavior Analytics (ABA) with Praxen and Observra creates a comprehensive security lifecycle for autonomous machine identities.

• Standardizing Agent Telemetry with Observra: Active AI agents generate complex, unstructured activity logs. Observra acts as an open-source SDK and logging library that captures runtime agent operations, including model calls, prompt details, tool usage, system costs, and errors. It normalizes this data into a structured event format, providing the consistent telemetry stream required for advanced threat detection.
• Verifying Agent Policies with Praxen: Before an agent is deployed, Praxen serves as an open-source reference implementation for Agent Behavior Verification (ABV). It compares the declared security policy of an AI agent against its actual underlying code, deployment state, and initial behavioral logs. This ensures that discrepancies, logic flaws, or unauthorized capabilities are flagged before the agent enters production.
• Continuous Behavioral Analysis with ABA: During active operations, the ABA engine ingests normalized telemetry from Observra and leverages the policy baselines established by Praxen. The engine applies machine learning models to build behavioral baselines for each agent, scoring risks and flagging real-time anomalies. If an agent drifts from its intended role, calls unapproved tools, or accesses unauthorized data, ABA immediately raises risk scores and triggers alerts.

This combined approach allows security teams to verify AI agent behavior prior to deployment and maintain continuous, baseline-driven visibility throughout active operations.

Learn how Exabeam UEBA can extend behavioral detection to every identity in your environment, including non-human identities and AI agents, by exploring the Exabeam User and Entity Behavior Analytics capabilities page.