What is a Non-Human Identity (NHI)?
For years, cybersecurity teams focused primarily on protecting human identities such as employees, contractors, partners, and administrators. Identity and Access Management (IAM) programs were built around authenticating and authorizing people.
Today, however, machines are increasingly accessing systems, applications, APIs, cloud resources, and data without direct human involvement. These machine identities are known as Non-Human Identities (NHIs).
As organizations adopt cloud computing, automation, DevOps, APIs, AI applications, and AI agents, the number of non-human identities often exceeds human identities by a factor of 20, 50, or even 100 times. As a result, NHIs have become one of the fastest-growing attack surfaces in modern cybersecurity.
A Non-Human Identity (NHI) is a digital identity used by applications, services, workloads, scripts, containers, APIs, devices, or AI systems to authenticate and interact with other systems. Unlike human identities, NHIs are designed for machines rather than people.
Examples include:
- Service accounts
- API keys
- Access tokens
- OAuth credentials
- Cloud workload identities
- Kubernetes service accounts
- Secrets and certificates
- Robotic Process Automation (RPA) accounts
- AI agents
- Machine-to-machine authentication credentials
These identities enable automated systems to securely communicate and perform tasks without requiring direct human interaction.
Why Are Non-Human Identities Important?
Modern enterprises depend heavily on automation. Applications continuously communicate with:
- Cloud services
- Databases
- Internal APIs
- SaaS platforms
- AI models
- Data repositories
- Development pipelines
Every connection requires authentication. As organizations scale their digital operations, the number of machine identities grows rapidly. In many environments, security teams discover thousands or even millions of NHIs operating across cloud and on-premises infrastructure. Managing these identities has become a major security challenge.
Examples of Non-Human Identities
API Keys
Applications often use API keys to authenticate with external services. For example, a customer portal may use an API key to access a payment processing platform.
Service Accounts
Applications frequently rely on service accounts to access databases, cloud storage, and internal systems.
Cloud Workload Identities
Cloud-native applications use workload identities to authenticate workloads without requiring hardcoded credentials.
Kubernetes Service Accounts
Containers and microservices often use Kubernetes service accounts to communicate within cloud environments.
AI Agents
AI agents increasingly interact with enterprise applications, databases, APIs, and business systems. Each AI agent requires its own identity and permissions to perform actions autonomously.
Why NHIs Create Security Risks
Many organizations have mature processes for managing employee accounts. However, non-human identities are often managed very differently. As a result, NHIs frequently become security blind spots.
Excessive Permissions
Many machine identities receive far more permissions than necessary. An application may retain broad administrative access long after deployment.
Forgotten Credentials
API keys, service accounts, and tokens are often created but never reviewed or removed. Over time, these dormant credentials become security risks.
Credential Exposure
Developers sometimes accidentally expose secrets, API keys, or tokens in:
- Source code repositories
- Configuration files
- CI/CD pipelines
- Cloud storage locations
Threat actors actively search for these exposed credentials.
Lack of Visibility
Organizations often do not know:
- How many NHIs exist
- What permissions they have
- Which systems they access
- Whether they are still required
Without visibility, managing risk becomes extremely difficult.
Why AI is Increasing NHI Risks
The rise of AI is creating an explosion of new machine identities. AI systems increasingly rely on:
- AI agents
- Autonomous workflows
- Multi-agent systems
- Retrieval-Augmented Generation (RAG) applications
- Model integrations
- External APIs
Every AI-driven interaction requires authentication and authorization. As organizations deploy more AI-powered services, the number of NHIs grows significantly. An AI agent may access:
- Knowledge bases
- CRM systems
- Cloud storage
- Internal databases
- Business applications
- Third-party APIs
Without proper governance, these identities can gain excessive access to sensitive information. This is one reason why Non-Human Identity Security has become a growing focus within AI security programs.
NHI vs. Human Identity
Human Identity | Non-Human Identity |
|---|---|
Represents a person | Represents a machine, application, or service |
Authenticates users | Authenticates systems and workloads |
Managed through traditional IAM | Requires machine identity management |
Typically has known ownership | Ownership is often unclear |
Easier to inventory | Often difficult to discover and track |
The challenge is not simply the number of NHIs, but also the speed at which they are created and modified.
Common NHI Security Challenges
Organizations often struggle with:
- NHI sprawl
- Excessive permissions
- Credential rotation
- Secret management
- Cloud complexity
- Multi-cloud visibility
- AI agent governance
- Identity ownership tracking
These challenges continue to grow as automation and AI adoption accelerate.
How Organizations Manage NHIs
Modern NHI security programs typically focus on four key areas.
Discovery
Identify all machine identities across cloud, on-premises, SaaS, and AI environments.
Inventory Management
Maintain visibility into ownership, permissions, usage, and lifecycle status.
Least-Privilege Access
Ensure NHIs receive only the permissions required to perform their intended functions.
Continuous Monitoring
Monitor machine identities for excessive permissions, unusual activities, credential exposure, and unauthorized access attempts. Continuous monitoring helps reduce the likelihood of identity-related attacks.