Non-Human Identity Security: The Machine Identity Crisis
Saniya Khatri
A non-human identity is any digital identity used by software rather than a person, such as an API key, service account, or AI agent credential, and these identities now outnumber human employees by more than 100 to 1 in the average enterprise.
What Are Non-Human Identities, and Why Have They Exploded?
The Governance Gap: Why Machine Identities Slip Through the Cracks
How Non-Human Identities Actually Get Exposed
Why AI Agents Make This Problem Harder, Not Easier
How Vectoredge Helps You Close the Non-Human Identity Gap
Frequently Asked Questions About Non-Human Identity Security
What Are Non-Human Identities, and Why Have They Exploded?
A non-human identity, often shortened to NHI, is any credential-bearing entity that software uses to authenticate and access systems without a person directly typing a password. This includes API keys, service accounts, OAuth tokens, SSH keys, certificates, and increasingly, autonomous AI agents that log in, call APIs, and move data on their own schedule.
According to Palo Alto Networks' 2026 Identity Security Landscape report, machine identities now outnumber human identities by 109 to 1 in the average enterprise, up from 82 to 1 just a year earlier. Other research shows a similar picture at different scales: Rubrik Zero Labs places the ratio at 45 to 1 across the modern enterprise, while Entro Labs' 2025 research found it reaches 144 to 1 in cloud-native and DevOps environments specifically.
The growth driver is unmistakable. Of every 109 machine identities per human employee, roughly 79 are AI agents, meaning AI agents alone account for close to 73% of all non-human identities in a typical organization today. Every new automation, integration, or AI agent an organization deploys quietly creates one or more new identities that need a credential, a permission set, and a lifecycle, whether anyone tracks it or not.
The Governance Gap: Why Machine Identities Slip Through the Cracks
Human identity management is mature. Employees get onboarded through HR-linked workflows, get multi-factor authentication by default, and get deprovisioned the day they leave. Non-human identities typically get none of this. A developer creates a service account to unblock a deployment, a script inherits broad permissions because narrowing them would take longer, and the credential outlives the project that created it.
The Cloud Security Alliance found that the non-human identity population grew 44% between 2024 and 2025, a pace that governance programs have not kept up with. Unlike human credentials, non-human identities often lack MFA enforcement, rotate infrequently if ever, and operate with standing, broad permissions rather than time-boxed, least-privilege access.
This creates what security researchers now call zombie secrets: credentials tied to decommissioned projects, former employees, or retired integrations that were never revoked. They sit in code repositories, CI/CD pipelines, and configuration files, fully functional and almost entirely unmonitored, waiting for anyone who finds them.
Ownership is the other half of the gap. A human account always has a named owner who can be asked why it needs certain access. A service account created eighteen months ago by an engineer who has since changed teams often has no clear owner left to answer that question, so security teams default to leaving it alone rather than risking an outage by revoking access nobody can confirm is safe to remove.
How Non-Human Identities Actually Get Exposed
Non-human identity exposure is not a rare event. According to GitGuardian's State of Secrets Sprawl 2026 report, 28.65 million new hardcoded secrets were pushed to public GitHub repositories in 2025 alone, a 34% year-over-year increase and the largest single-year jump on record. Secrets tied specifically to AI services, including AI API keys, agent configuration tokens, and LLM service credentials, grew 81% year over year, the fastest-growing credential category GitGuardian tracks.
SpyCloud's 2026 Identity Exposure Report found a similar surge from the attacker's side: 18.1 million exposed API keys and tokens were recaptured from criminal sources in 2025, spanning cloud infrastructure, payment platforms, developer tools, and AI services, alongside 6.2 million credentials or authentication cookies tied specifically to AI tools.
Once a non-human identity is exposed, it is often more valuable to an attacker than a stolen employee password. A leaked API key or service account credential can provide direct, persistent, and often unmonitored access to production systems, customer data, and software supply chains, without triggering the login alerts or anomaly detection built around human user behavior.
Why AI Agents Make This Problem Harder, Not Easier
Traditional non-human identities, like a backup script's service account, have narrow, predictable behavior. An AI agent's identity is fundamentally different: it may need to call dozens of different APIs, access multiple data sources, and make autonomous decisions about what to retrieve or act on next, all under a single set of credentials.
This is a least-privilege problem at a scale most identity programs were never built for. Granting an AI agent broad standing access because its exact future needs are hard to predict in advance is the same mistake that created today's human over-permissioning problem, except now it is multiplied across potentially thousands of agent identities instead of a fixed employee headcount.
Palo Alto Networks projects machine identities will grow 77% over the coming period, compared to 56% growth in human identities, meaning the ratio gap is on track to widen further, not close. Every organization deploying agentic AI is, in effect, adding new privileged accounts faster than it can govern the ones it already has.
Multi-agent workflows compound this further. When one AI agent calls another agent, which in turn calls a third-party API, a single user-initiated action can trigger a chain of machine-to-machine authentication events with no human in the loop to notice if one hop in that chain reaches further into sensitive data than the original task required.
How Vectoredge Helps You Close the Non-Human Identity Gap
Vectoredge treats non-human identity risk as a data security problem, not just an access-management checkbox. The question that matters is not only which service account exists, but what sensitive data that account, API key, or AI agent can actually reach, and whether that access is still justified.
Vectoredge helps security teams map machine identities back to the sensitive data they touch, flag standing permissions that exceed what an integration or agent actually uses, and surface exposed or dormant credentials before they become the entry point for a breach. This closes the visibility gap that lets zombie secrets and over-permissioned agents persist unnoticed for months.
Non-human identities are not going away, and blocking automation or AI adoption is not a realistic answer. The organizations that manage this well are the ones that pair AI and automation growth with equally fast growth in the visibility and governance covering it.
Frequently Asked Questions About Non-Human Identity Security
What is a non-human identity?
A non-human identity is any digital identity used by software rather than a person to authenticate and access systems, including API keys, service accounts, OAuth tokens, certificates, and AI agent credentials.
How many machine identities does the average enterprise have compared to humans?
Palo Alto Networks' 2026 Identity Security Landscape report found machine identities outnumber human identities by 109 to 1 on average, up from 82 to 1 the prior year, with other research placing the ratio between 45 to 1 and 144 to 1 depending on the environment.
Why are AI agents a bigger identity risk than older automation?
AI agents typically need broader, less predictable access across multiple systems than a traditional script, which makes it harder to apply least-privilege access and easier to over-permission them by default.
What is a zombie secret?
A zombie secret is a credential, such as an API key or service account token, tied to a decommissioned project, former employee, or retired integration that was never revoked and remains active and exploitable.
How can organizations reduce non-human identity risk?
By mapping every machine identity to the actual data and systems it touches, enforcing least-privilege and credential rotation, and continuously monitoring for exposed or dormant secrets rather than relying on a one-time audit.
What’s Next?
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Saniya Khatri
Saniya Khatri is a cybersecurity research and analytics professional at Vectoredge, with four years of expertise in analyzing emerging threats and crafting actionable insights. Specializing in AI-driven attacks, data protection, and insider risk, Saniya empowers organizations to navigate the evolving threat landscape with confidence.
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