What are best practices for non-human identity management?

Key Takeaways

• Non-human identities now outnumber human identities by large margins, making machine identity governance a foundational security requirement.
• OWASP added non-human identities as a dedicated security focus because unmanaged machine identities create expanding attack paths across cloud and SaaS environments.
• Effective non-human identity management requires organizations to discover identities, understand permissions and risk, then enforce governance controls continuously.
• In an IBM survey, 77% of organizations reported AI adoption is already outpacing current governance capabilities.

What Are Best Practices for Non-Human Identity Management?

Effective non-human identity (NHI) management combines continuous discovery, least privilege, permission monitoring, and lifecycle governance. As cloud automation and AI adoption grow, organizations should:

• Continuously discover NHIs across cloud, SaaS, Kubernetes, CI/CD, and AI environments.
• Understand permissions, ownership, trust relationships, and potential blast radius.
• Enforce least privilege through regular access reviews, credential rotation, and automated remediation.
• Govern identities throughout their lifecycle by removing unused credentials and monitoring for privilege drift.

Quick Facts: 5 Non-Human Identity Management Risks Every Security Team Should Track

Why Non-Human Identity Management Has Become Essential

Non-human identities power cloud automation, applications, and AI agents, but they often accumulate access faster than organizations can govern it.

Consider a cloud optimization agent that starts with limited permissions and gradually gains access to repositories, cloud resources, and operational systems through additional service accounts, API keys, and OAuth grants.

Eventually, security teams can no longer answer a simple question: What can this identity access, and what happens if it is compromised?

This scenario reflects a broader challenge facing modern cloud environments. As cloud automation, Kubernetes, CI/CD pipelines, SaaS integrations, and AI adoption accelerate, machine identities are created faster than organizations can discover, understand, and govern them.

As identities and integrations multiply, visibility declines. Organizations struggle to discover, understand, and govern a rapidly expanding population of service accounts, API keys, OAuth tokens, workload identities, and AI agents. Reflecting that growth, GitGuardian's State of Secrets Sprawl Report 2026 found more than 28 million new secrets exposed in public GitHub repositories in a single year.

The challenge is no longer creating machine identities. It's governing them.

Why Does Poor Non-Human Identity Management Create Risk?

Every non-human identity represents an access path into an organization's environment. Service accounts, API keys, OAuth grants, workload identities, and AI agents connect cloud resources, applications, and operational systems.

As permissions accumulate over time, organizations lose visibility into their true attack surface. OWASP highlights this challenge through the OWASP Non-Human Identity Top 10, which includes risks such as secret leakage, excessive privileges, and lifecycle management failures.

Attackers increasingly target machine identities because they often receive less oversight than human accounts.

The 2024 BeyondTrust incident demonstrated how compromised credentials and access paths can become entry points for broader attacks. While every breach differs, the lesson is consistent: access granted to machines must be governed with the same rigor as access granted to people.

How Can Organizations Effectively Manage Non-Human Identities?

Regaining control begins with visibility. Organizations must first discover every non-human identity before they can assess risk or enforce governance.

Discover Every Identity

Effective non-human identity management begins with discovery. In our cloud optimization example, the first challenge is identifying every identity that enables the agent to operate, from service accounts and API keys to OAuth applications and cloud roles.

As access expands across systems, visibility declines. Without a complete inventory of identities and credentials, security teams cannot assess risk, establish ownership, or enforce governance. Discovery is the foundation of effective non-human identity management.

Determine What Access Those Identities Have

The next step is ensuring visibility to illuminate risk. Security teams must understand what the cloud optimization agent can access, what permissions it holds, and the potential blast radius if a credential is compromised. Palo Alto researchers estimate that 99% of cloud identities have excessive permissions, opening companies up to unexpected risk.

Apply Controls Consistently

Once identities and access are understood, teams can reduce risk by eliminating unnecessary permissions, retiring stale credentials, addressing exposed secrets, and monitoring for suspicious behavior.

Bringing It All Together

Effective non-human identity management requires organizations to discover identities, understand permissions and risk, and enforce controls continuously. In our cloud optimization scenario, each step is essential to maintaining visibility and control as access expands over time.

How to Improve Management with Four NHI Best Practices

As cloud and AI environments expand, non-human identities often accumulate privileged access that is rarely reviewed or removed. The Cloud Security Alliance found that 85% of credentials with elevated privileges had not been used in the previous 90 days, creating unnecessary attack surface. Organizations can reduce that risk by following four best practices that continuously discover, govern, and secure non-human identities throughout their lifecycle.

Establish Ownership for Every Identity

Every identity associated with the cloud optimization agent should have a documented owner responsible for approving access and reviewing permissions. Unknown ownership often leads to abandoned credentials, orphaned service accounts, and delayed remediation.

Apply Least Privilege Continuously

The agent may need billing visibility but not infrastructure modification rights. Regular entitlement reviews help prevent permission accumulation as integrations expand.

Govern AI Agents as Identities

The cloud optimization agent illustrates why AI agents should be treated as first-class identities. Every agent requires authentication, authorization, lifecycle management, activity monitoring, and periodic permission reviews.

Measure Blast Radius

If the cloud optimization agent were compromised today, what is the blast radius? Can that agent modify infrastructure, access source code, or retrieve sensitive data? SANS reported in its 2026 SANS AI Survey that 60% of respondents reported significant AI shortcomings in threat detection and response, up from 45% in 2025.

How Token Security Approaches Non-Human Identity Management

Intent-based security provides the foundation for effective non-human identity management by continuously discovering identities, analyzing permissions, and ensuring access remains aligned with each identity's intended purpose.

The Challenge

Organizations struggle to answer three critical questions:

• What machine identities exist?
• What permissions do they have?
• Which identities create the greatest risk?

Traditional IAM and PAM products were built primarily for human users. They were not designed to govern machine identities operating at cloud scale.

The Approach

Token Security applies a machine-first security approach built around three core principles:

Discover

Identify non-human identities across cloud providers, SaaS applications, development platforms, secrets stores, and AI environments.

Understand

Map entitlements, analyze blast radius, establish behavioral baselines, and identify risky access relationships.

Enforce

Once organizations understand which identities exist and the risks they present, they can begin enforcing controls. Token Security helps teams govern machine identities throughout their lifecycle, automatically remediate common exposures, and continuously reduce unnecessary access.

• Identity discovery reveals what exists
• Entitlement mapping shows who or what has access
• Blast-radius analysis highlights potential impact
• Behavioral baselines help detect unusual activity before it becomes a larger problem

The Outcome

Organizations gain visibility into machine identities, reduce excessive permissions, shorten remediation timelines, and establish governance controls that scale alongside cloud adoption and AI initiatives.

Turning Machine Identity Visibility into Control

These examples show how organizations are applying machine-first security and NHI best practices to improve visibility, reduce risk, and govern AI-driven access.

Finding Actionable Machine Identity Risk

A large digital insurance provider needed better visibility into machine identity risk across a rapidly growing environment.

"Token Security has enhanced our security by providing us accurate and relevant visibility into machine identity risks, something I have yet to see from other vendors. It's the first service I've seen that delivers on the widely-made claim of finding machine identity risk. It provides us with the right amount of detail to mitigate issues without burdening us with tens of rows of useless alerts." — Jonathan Jaffe, CISO at Lemonade

The result is greater visibility into machine identity risk and faster, more effective remediation.

Governing AI Agents with Confidence

This experience highlights a common challenge: visibility without actionable context rarely improves security outcomes. Security teams need meaningful risk prioritization to properly manage non-human identities, not additional noise.

As AI adoption accelerated, another organization needed governance over custom GPT agents operating throughout the environment.

"Token Security gives us visibility we simply didn't have before. We can now automatically identify and control custom GPT agents running in our environment and ensure the required security level. Knowing that no AI agent is operating beyond our oversight means we can confidently accelerate our AI adoption." — Tamir Ronen, Global CISO at HiBob

This example reinforces a growing reality. AI governance depends on understanding the identities, permissions, and credentials that allow autonomous systems to operate.

Why Non-Human Identities Require a New Security Model

The cloud optimization agent began as a simple automation project. Over time, it accumulated identities, permissions, credentials, and access relationships that few people fully understood.

That pattern is becoming increasingly common as organizations deploy AI agents and automation at scale. The challenge is no longer managing individual credentials. It is governing the non-human identities that power modern business operations.

Organizations that discover identities, understand permissions and risk, and enforce continuous governance will be better positioned to manage non-human identities and adopt AI safely while reducing exposure across their environments.