Human vs. Non-Human Identity: The Key Differentiators
Published on
March 25, 2025
Felipe Araujo
9+ years of B2B marketing, I have contributed to big brands online strategy.
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Digital identities have evolved far beyond usernames and passwords for employees and customers. Behind every modern organization's firewall lurks a vast, often unmanaged population of service accounts, API keys, bots, and machine identities that outnumber human users by orders of magnitude. These non-human identities (NHIs) represent both the backbone of digital transformation and an expanding attack surface that security teams must urgently address.
Understanding Human and Non-Human Identities
Human identities represent individuals with specific roles and responsibilities within an organization. They include employees, contractors, partners, and customers who interact with systems based on their job functions or relationships with the company. Non-human Identities encompass all digital identities not directly tied to an individual person. Here's some examples below:
While human identities typically follow traditional Identity and Access Management (IAM) frameworks, non-human identities operate under different paradigms that require specialized security approaches. The most significant security challenges emerge not from treating each type separately, but from failing to recognize their fundamental differences.
Core Differentiators Between Human and Non-Human Identities
Operational Characteristics
Human identities are characterized by:
Predictable usage patterns: Typically work during business hours with consistent access needs
Cognitive decision-making: Can interpret contextual security factors and exercise judgment
Self-management capabilities: Can reset passwords, request access, and report issues
Limited parallel operations: Only one session or action at a time
Natural velocity limits: Human-speed interactions with systems
Non-Human Identities operate with:
Programmatic behavior: Follow defined algorithms without discretion
Continuous operation: Often run 24/7 without breaks
High-volume automation: Can execute thousands of operations per second
Parallel processing: Multiple simultaneous connections and actions
No inherent self-management: Cannot independently manage their own credentials
Authentication & Authorization Differences
Human identities authenticate through:
Knowledge factors: Passwords and security questions
Possession factors: Mobile devices, security tokens
Decentralized management: Created by developers, operations teams, and automated processes
Hidden existence: Often undocumented and untracked
Limited constraints: Can multiply rapidly with new technology adoption
Environment-specific proliferation: Multiple identities for different environments (dev/test/prod)
Monitoring Capability Differences
Human identities are monitored through:
Behavioral analysis: Unusual login times or locations
Activity thresholds: Number of actions or sessions
Authentication anomalies: Failed login attempts
Device profiling: Tracking authorized devices
Training effectiveness: Response to security awareness initiatives
Non-Human Identities require monitoring of:
Volume metrics: Unusual API call frequency
Resource utilization: Abnormal compute or data access
Permission utilization: Using dormant or rare privileges
Connection patterns: New or unusual connection sources
Execution anomalies: Deviations from expected operational patterns
Credential age: Identifying stale or long-lived secrets
The Critical Role of Secret Detection in Identity Security
The distinctions between human and non-human identities extend far beyond access patterns and authentication methods; they shape the very foundation of modern security strategies. While traditional identity management focuses on protecting human credentials, the explosive growth of non-human identities introduces a far greater challenge: the proliferation of embedded secrets scattered across code, infrastructure, and automation workflows.
This expanding attack surface demands a dedicated approach to secret detection. Hardcoded API keys, long-lived service account credentials, and mismanaged tokens are among the most common sources of breaches, yet they often go unnoticed until it’s too late. Consider these risks:
Over 6 million secrets leak on GitHub annually.
The average enterprise has thousands of exposed credentials lurking in its code repositories.
85% of breaches involving non-human identities originate from leaked secrets.
Without continuous, proactive secret detection, organizations risk silent but devastating compromises. Modern security solutions, like Cremit, integrate automated scanning across development environments, collaboration tools, and runtime systems to identify and remediate exposures before attackers exploit them.
Secure Your Non-Human Identities Now
NHIs outnumber human users in most environments, yet they often go unprotected. Embedded secrets in code, infrastructure, and automation workflows create serious security risks.
Start securing your secrets today with Cremit’s solution. Get started now or schedule a demo to see how Cremit helps protect non-human identities at scale.
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Explore the critical differences between human and non-human digital identities, revealing hidden security risks and the importance of secret detection.
