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For every person in an organization, there are about 92 non-human identities. These range from service accounts and API keys to automated workflows. However, the landscape is evolving even further with the introduction of AI agents acting on their own.
It is the sheer volume of non-human identities (NHIs), combined with the emerging independent decision-making of AI agents, that is now creating your biggest security risk.
Non-human identities (NHIs) have become both the foundation of automation and the weakest link in enterprise security. Their volume, persistence, and invisibility make them ideal entry points for attackers and difficult for defenders to detect.
Addressing this requires a shift in mindset from treating machine credentials as background utilities to managing them as first-class identities with defined lifecycles, policies, and monitoring.
If machines now drive your business, your identity strategy must evolve. Let’s gain a deeper understanding of what NHIs are and why they are now one of the most critical cybersecurity risks.
What are non-human identities?
Non-human identities (NHIs) are digital credentials used by machines, applications, and automated processes to authenticate, communicate, and access data. They represent any entity that isn’t a person but still needs an identity to operate securely within an IT environment.
Common examples include service accounts, API keys, certificates, OAuth tokens, workload identities for containers and cloud functions. Each of these entities carries permissions and access rights similar to a human account, and therefore poses comparable security risks
Non-human identities vs. human identities
Human identities represent individual users like employees, contractors, or partners, who authenticate through usernames, passwords, and multi-factor authentication. They have defined lifecycles managed through HR systems and access governance processes: onboarding, role changes, and offboarding.
Non-human identities, by contrast, belong to machines, applications, and digital services that need to communicate or perform actions autonomously. They authenticate using keys, tokens, or certificates, rather than passwords, and they rarely have a formal lifecycle or assigned owner.
While human accounts are typically few in number and centrally governed, non-human identities can number in the tens or hundreds of thousands, often created by scripts, cloud workloads or development pipelines.
Non-human identities:
- Don’t expire naturally
- Operate continuously
- Can access critical systems without human intervention
This scale and autonomy make NHIs both indispensable and risky. Managing them requires visibility, lifecycle controls, and governance mechanisms that traditional human-focused IAM programs were never designed to handle.
Types of non-human identities
Non-human identities appear across every layer of modern IT infrastructure from cloud services to DevOps pipelines. While they differ in purpose and scope, all serve the same function: enabling machines to authenticate and perform trusted actions without human intervention. The most common types of non-human identities include:
- Service accounts: Used by applications or workflows to access databases, servers, or APIs. These accounts often hold elevated privileges and are sometimes shared or hardcoded, making them difficult to track and secure.
- API keys and tokens: Facilitate data exchange and system-to-system communication. When exposed in code repositories or logs, they can give attackers direct access to sensitive services.
- Certificates and cryptographic keys: Establish trust and encrypt communication between devices, applications, and services. Poor rotation or expired certificates can lead to service outages or exploitation through impersonation.
- Workload identities: Assigned to containers, virtual machines, and cloud functions. They enable cloud-native workloads to authenticate securely but can proliferate quickly without centralized governance.
- Bots and automation scripts: Operate in IT operations, monitoring, and customer support environments. Each bot or script typically authenticates using embedded credentials or tokens.
The Evolution: From Static Credentials to AI Agents
It is important to distinguish between the static credentials listed above and the emerging threat of AI Agents.
While AI agents utilize non-human identities (like API keys and service accounts) to perform their tasks, they represent a separate, higher-order category of risk. Unlike a standard script that follows a linear set of instructions, AI agents possess agency. They can make independent decisions, generate new workflows, and interact across systems in unpredictable ways.
We view AI agents not merely as another “type” of NHI, but as autonomous operators that use NHIs to function. This introduces a new layer of complexity: you must secure not only the credentials (the NHI) but also the intent and behavior of the agent using them.
Why non-human identities (NHIs) are prime targets for cyberattacks
Non-human identities are increasingly attractive to cybercriminals, largely because of their extensive, often unmonitored, access to corporate systems. Unlike human users, these identities often operate in the background without the same level of security scrutiny, making them easy to exploit. This lack of oversight creates critical vulnerabilities that attackers are keen to leverage.
Attackers often use compromised NHIs to:
- Steal credentials: Without standard security measures like multi-factor authentication, NHIs are highly susceptible to credential theft. This makes them a primary target for brute force attacks, as their access can grant attackers a foothold in your network.
- Elevate privileges: Once an attacker gains control of a non-human identity, they can often use it as a stepping stone to gain higher-level permissions. By exploiting outdated software or other vulnerabilities, they can escalate privileges to access more sensitive data and systems.
- Move laterally: A compromised NHI is often the first step in a larger attack. Because these identities are so interconnected with APIs, databases, and other network resources, an attacker can use a single compromised identity to move freely across the network, install malware, create backdoors, or disable security protocols.
The impact of non-human identities on cybersecurity
The rise of non-human identities has quietly redefined the attack surface. What was once a manageable perimeter of human users and devices has evolved into a sprawling web of machine-to-machine connections, many of which operate without visibility, ownership, or security controls.
Though 69% of organizations are concerned about attacks from non-human identities, only 15% feel confident in their ability to prevent them, revealing a significant gap between awareness and preparedness.
- Expanded attack surface
Machine identities are often created automatically through scripts, DevOps pipelines, or cloud provisioning. As a result, organizations accumulate thousands of keys, tokens, and service accounts, many of which are forgotten, used, or hardcoded in source code.
Compromised machine credentials are increasingly leveraged for lateral movement and privilege escalation inside hybrid environments. Attackers no longer need to phish an employee when they can steal an API key that unlocks entire systems.
- Persistent, unmonitored access
Unlike human accounts, non-human identities don’t retire or rotate credentials on their own. Many persist for years with privileged access, far beyond their intended purpose. These long-lived credentials with invisible lifecycles are accounts that rarely get trigger alerts because they behave like expected automation.
This persistence allows attackers to maintain undetected access for extended periods once a machine identity is compromised.
- Blindspots in traditional IAM and monitoring tools
Legacy IAM frameworks were designed around human users, with controls built for login events, MFA, and HR-driven provisioning. Non-human identities, however, authenticate differently. They often authenticate without sessions, prompts, or MFA.
Most organizations’ IAM tools cannot distinguish between legitimate machine activity and credential misuse because they lack behavioral context for automated accounts. This gap enables attackers to blend in with normal machine traffic.
- Chain reaction risk across integrated systems
Modern environments are deeply interconnected through APIs and automation workflows. A single compromised service account or token can cascade across multiple platforms.
For example, a compromised CI/CD pipeline token might allow an attacker to inject malicious code into production systems, transforming a single machine identity breach into a multi-environment compromise.
- Compliance risks
Mismanaged NHIs can also have compliance and operational implications. Expired certificates can cause critical service outages, while unauthorized API access can expose sensitive data in violation of privacy and security standards. The challenge is not only technical but also one of the governance and accountability.
What makes it so hard to manage non-human identities?
Lack of visibility
One of the most fundamental challenges with NHIs is simply knowing what exists. Unlike human users, non-human identities are created continuously by developers, automation tools, or cloud services, often without oversight.
Most organizations remain unaware of where credentials reside, who created them, or what systems they access. This identity sprawl leads to dormant, orphaned, or duplicate credentials that attackers can easily exploit.
Unclear ownership
Human accounts have clear owners while NHIs often do not. Service accounts may belong to a team, a script, or a third-party integration, but no single person is responsible for their security. This creates a governance gap as machine identities fall between operational teams, developers, and security, leading to inconsistent management.
Without defined ownership, it becomes difficult to enforce access policies, rotate credentials, or decommission unused accounts.
Privilege creep
Many non-human identities are created with broad or permanent access because restricting permissions can disrupt automation. This results in privilege creep where machine accounts accumulate unnecessary rights over time.
Inadequate credential hygiene and lifecycle management
Most machine credentials are static, such as long-lived API keys, unrotated certificates, or hardcoded secrets embedded in scripts. These are difficult to audit and even harder to rotate without breaking automated workflows.
Organizations often prioritize uptime over credential hygiene, leaving aging keys and certificates in production long after they should have been replaced. Each of these becomes a potential backdoor for attackers.
Tooling gap
Traditional IAM, PAM, and identity threat detection and response (ITDR) solutions were built for humans, relying on logging patterns, MFA, and HR-driven provisioning. Non-human identities don’t fit those models.
Most organizations still manage machine identities through ad-hoc spreadsheets or isolated systems. The result is fragmented visibility, inconsistent policy enforcements, and limited integration with existing security workflows.
The next frontier in identity security
Non-human identities have quietly become the backbone of modern IT, yet they remain one of its least visible risks. As automation accelerates, these machine identities multiply faster than the tools designed to control them, creating silent entry points for attackers.
For IT and security leaders, the challenge is no longer just managing who has access, but what does. Securing this new layer of machine-to-machine trust requires rethinking visibility, authentication, and governance beyond users to every digital entity operating in the enterprise.
To gain a deeper insight around the topic:
Explore our ebook “Who Let The Bot In?” to understand the emerging risks of autonomous AI agents, real-world examples of where it’s gone wrong, and the steps you can take to apply identity-first governance.
