Modern businesses rely on thousands of automated processes, from service accounts to AI agents, that operate without human intervention. These non-human identities (NHIs) now significantly outnumber human users, creating a vast and often unmonitored attack surface that traditional security tools struggle to manage.
As organizations adopt more cloud services and artificial intelligence, the number of these autonomous identities is growing exponentially. Many are created with excessive permissions and without clear ownership, posing a substantial and evolving threat to enterprise security.
Key Takeaways
- Non-human identities, including service accounts and AI agents, can outnumber human employees by more than 80 to 1 in many organizations.
- Unlike human users, NHIs lack context like location or device, making it difficult to apply modern security controls like multi-factor authentication.
- Many NHIs are created with overly broad permissions and are never reviewed or de-provisioned, creating permanent security vulnerabilities.
- Autonomous AI agents introduce new risks as they can make decisions and access sensitive data without direct human oversight.
- Security teams are moving toward unified identity platforms to discover, manage, and govern these automated identities.
The Expanding Landscape of Digital Identities
In today's digital infrastructure, the workforce extends far beyond human employees. A silent, automated workforce of non-human identities executes critical background tasks 24/7. These include service accounts that sync data between applications, API tokens that grant access to services, and increasingly, AI agents that perform complex operations autonomously.
The shift to cloud-native architectures has accelerated the creation of these identities. Automated deployment scripts and microservices often generate new accounts and credentials on the fly. While this automation boosts efficiency, it frequently bypasses traditional security oversight.
A Numbers Game
According to security analysts, the ratio of non-human to human identities in some cloud-intensive environments can exceed 80-to-1. This sheer volume makes manual tracking and management practically impossible.
The primary issue is a lack of visibility and ownership. Security teams often ask, "Who created this service account? What data does it access? Is it still needed?" In many cases, the answers are unknown. These identities become digital ghosts within the network, active but unaccounted for.
Why AI Agents Present a Unique Challenge
While service accounts and API keys have been a known risk for years, the rapid adoption of artificial intelligence introduces a new and more unpredictable class of non-human identity. Unlike older machine identities that follow predefined scripts, AI agents are designed for autonomy.
Autonomous Decision-Making
AI agents can interact with systems, query databases, and initiate actions based on their programming without direct commands. This autonomy requires them to have access to sensitive information and powerful APIs, but few organizations have established clear rules to govern their behavior.
An AI agent integrated into a customer service platform might need access to user data to function. However, without strict controls, it could potentially access more information than necessary, creating a significant data privacy and security risk if compromised.
The Context Deficit in Machine Identities
Modern security for human users relies heavily on context. A login attempt from an unusual location or a new device can trigger an alert or a request for multi-factor authentication (MFA). Non-human identities operate without this context. They are simply code running on a server, making it difficult to distinguish legitimate activity from a malicious actor using stolen credentials.
Furthermore, AI agents often lack a clear lifecycle. They can be deployed by individual developers, embedded in third-party software, or activated via external APIs. Once active, they may run indefinitely with persistent credentials, creating a permanent potential entry point for attackers.
Common Security Failures with Non-Human Identities
The gap between traditional identity management and the reality of automated systems leads to several recurring security vulnerabilities. These issues are not new, but their scale has made them a critical priority for security teams.
- Lack of Visibility: The most significant challenge is simply not knowing what exists. Many organizations lack a complete inventory of all NHIs in their environment, creating "shadow identities" that operate outside of security monitoring.
- Excessive Permissions: For convenience, developers often grant NHIs broad permissions to prevent future access errors. An account that only needs to read from one database might be given write access to the entire system, violating the principle of least privilege.
- Orphaned Accounts: When an application is decommissioned or the employee who created a service account leaves, the associated NHI is often left active. These orphaned identities become unmonitored backdoors into the network.
- Static Credentials: Many NHIs rely on long-lived, hardcoded credentials like API keys or tokens. If these secrets are exposed in code repositories or logs, they provide attackers with a direct path to sensitive systems.
"If an AI agent can authenticate, access data, and make decisions, it is an identity. And if that identity isn't governed, it's a liability," stated a recent report from identity management firm Okta, highlighting the need to redefine what constitutes a manageable identity.
These over-permissioned and unmonitored accounts are ideal targets for attackers. A compromised NHI can be used for lateral movement across a network, allowing a threat actor to escalate privileges and exfiltrate data without triggering alarms designed to detect suspicious human behavior.
Strategies for Regaining Control Over Automated Access
To address the growing risk from NHIs, security organizations are adopting a more proactive governance model. This approach treats every automated agent, script, and system as an identity that requires the same level of management as a human user.
1. Discover and Inventory Every Identity
The first step is to establish a comprehensive, real-time inventory. Modern identity platforms can scan cloud environments like AWS and GCP, as well as on-premise systems, to automatically discover all human and non-human identities. This process eliminates manual tracking in spreadsheets and provides a foundational view of the entire attack surface.
2. Prioritize and Remediate High-Risk Accounts
With a full inventory, teams can identify and prioritize the most significant risks. This involves analyzing which identities have excessive permissions, access sensitive data, or have been inactive for long periods. The goal is to systematically reduce privileges to align with the principle of least privilege, shrinking the potential impact of a compromise.
For high-risk identities, implementing controls such as automated credential rotation and just-in-time access is critical. For powerful AI agents, establishing a "kill switch" to terminate sessions immediately upon detecting anomalous behavior is becoming a necessary safeguard.
3. Automate the Identity Lifecycle
Just as human employees have onboarding and offboarding processes, NHIs require an automated lifecycle. Leading organizations are implementing policies where every new NHI is automatically assigned an owner, granted time-bound and scoped permissions, and logged in an auditable system. When a project ends or an application is retired, the associated identities are automatically deprovisioned to prevent orphaned accounts.
The Role of an Identity Security Fabric
A key challenge is that different platforms (cloud providers, CI/CD tools, AI services) manage identities in unique ways. A unified identity security fabric aims to solve this by creating a single control plane to manage all identities. This allows security teams to define access policies once and enforce them universally, reducing blind spots and simplifying governance across fragmented environments.
By treating non-human identities as first-class citizens in a security strategy, organizations can move from a reactive posture to proactive control. This shift is essential to secure modern, automated enterprises against an attack surface that is constantly expanding and evolving.