NHI sprawl and AI agent abuse are outpacing IAM controls

At a glance

What this is: This article argues that unmanaged NHIs, especially AI agents and machine credentials, have outgrown conventional access oversight and now create a major attack surface.

Why it matters: It matters because IAM, PAM, and lifecycle controls that were built around human-paced review cycles do not scale cleanly to machine identities, autonomous tooling, or secret sprawl.

By the numbers:

• Many organizations are managing 100 non-human identities for every single human identity, with some organizations reaching margins of 500 to 1.

👉 Read Akeyless's analysis of unmanaged NHIs, AI agents, and machine identity risk

Context

NHI sprawl is the operational problem at the centre of this article. Service accounts, API keys, OAuth tokens, secrets, and bots are being created faster than most organisations can inventory them, which means access is often granted before ownership, purpose, or expiry are defined.

That creates a governance gap across IAM, PAM, and lifecycle management. The article’s core claim is that machine-scale identity growth, combined with AI-assisted abuse of exposed credentials, turns unmanaged access into a persistent security condition rather than a temporary hygiene issue.

Key questions

Q: How should security teams govern unmanaged non-human identities at scale?

A: Start with continuous discovery, ownership assignment, and lifecycle controls across code, pipelines, cloud, and SaaS. Then pair that inventory with least privilege, automatic rotation, and offboarding so credentials do not outlive the system they support. A governance programme only works when every NHI has a purpose, an owner, and an expiry path.

Q: Why do service accounts and API keys create more risk when they are overprivileged?

A: Because a single exposed credential can become a broad access event if the identity can reach multiple systems or environments. Overprivilege turns discovery into impact, which is why permission scope matters as much as secret protection. Narrower entitlements reduce the damage when credentials are leaked, reused, or abused by attackers.

Q: What breaks when NHI lifecycle management is missing?

A: Credentials outlive the systems, teams, or workflows they were created for, creating zombie identities that remain usable long after the original need has passed. That weakens auditability, increases attack surface, and leaves organisations unable to prove who still has access. Lifecycle failure is often the point where hidden risk becomes permanent risk.

Q: How can organisations tell whether their NHI controls are actually working?

A: Look for reduced secret sprawl, fewer long-lived credentials, clear ownership records, and rapid offboarding when workloads are retired. If teams cannot account for where secrets live or whether they still work, the control programme is failing. Good NHI governance produces traceable access decisions, not just more tooling.

Technical breakdown

Why NHI discovery fails at machine scale

Discovery breaks down because NHIs are created outside the normal human identity lifecycle. Developers can spin up service accounts, tokens, and secrets directly in code, CI/CD pipelines, SaaS apps, or cloud consoles, often without central registration. That leaves no authoritative owner, no clean deprovisioning path, and no reliable way to know whether the credential is still active. Shadow identities become especially dangerous when they are reused across systems or embedded in automation. Practical implication: teams need continuous discovery across code, pipelines, cloud, and SaaS, not periodic inventory exercises.

Practical implication: move from periodic review to continuous NHI discovery across code, pipelines, cloud, and SaaS.

How secret zero and runtime trust shape NHI access

Secret zero is the trust problem that appears before a workload can authenticate for the first time. If the initial credential is hardcoded, shared, or manually distributed, the whole access chain inherits that weakness. The article points to native workload identity, such as cloud IAM roles or Kubernetes service accounts, as the starting point for safer machine authentication. From there, dynamic secrets and just-in-time access reduce the value of any single credential. Practical implication: replace static bootstrap secrets with native workload identity and ephemeral credentials wherever possible.

Practical implication: replace static bootstrap secrets with native workload identity and ephemeral credentials wherever possible.

Why AI agents intensify NHI governance pressure

AI agents are not just another workload category. They authenticate to services, retrieve data, and execute actions using tokens or dynamically issued credentials, which means they behave like high-frequency NHI consumers even when the automation looks benign. Once those agents can access SaaS APIs or MCP-connected tools, privilege discovery and misuse can happen at machine speed. The issue is not AI hype, it is that machine identities are now being exercised by systems that can chain actions faster than human oversight loops can react. Practical implication: treat AI agents as governed identities with scoped access, auditability, and behavioural constraints.

Practical implication: treat AI agents as governed identities with scoped access, auditability, and behavioural constraints.

NHI Mgmt Group analysis

NHI sprawl has become an accountability failure, not just an inventory problem. The article describes a world where service accounts, API keys, and bots are created “on the fly” and then forgotten. That is a governance failure because nobody can reliably answer who owns the credential, what system it protects, or when it should die. The result is a standing-access environment with no clean lifecycle boundary. Practitioners should treat unmanaged growth as a control-plane defect, not a discovery inconvenience.

Secret zero was designed for human-paced provisioning, and that assumption fails under machine identity churn. Traditional onboarding assumes a credential can be issued, reviewed, and rotated in a stable sequence. That assumption breaks when workloads are created programmatically and AI agents can authenticate, act, and disappear across rapidly changing environments. The implication is that least privilege cannot be reasoned about only at provisioning time. Practitioners need to rethink how trust is established when the identity source is ephemeral and machine-originated.

AI agents turn NHI governance from static credential control into runtime behavioural control. The article correctly places AI agents among the fastest-growing NHI categories because they do not just hold credentials, they consume and act on them repeatedly. That shifts the security question from “is the secret valid” to “is the actor staying within intended scope while it operates.” OWASP-NHI and NIST-CSF both matter here, but the practical issue is whether the programme can see abuse fast enough to matter. Practitioners should classify agent access as monitored runtime behaviour, not just secret inventory.

Broad privileges remain the easiest path from exposure to impact. The article’s warning about overblown permissions is consistent with the broader NHI risk pattern: credentials are often over-granted to avoid development friction. Once a secret is exposed, broad access turns a small leak into a system-wide incident. This is where lifecycle governance and least privilege converge. The real question for security leaders is whether their NHI programme can shrink privilege before compromise turns into lateral movement.

Named concept: identity blast radius is now the right way to think about NHI risk. The article shows that the issue is not only how many machine identities exist, but how much access each one can reach if compromised. A service account with unnecessary privileges, weak oversight, and no expiry can touch far more than its intended task. That is an identity blast radius problem. Practitioners should measure how much damage a single NHI can cause when discovery, rotation, and offboarding all lag behind usage.

From our research:

• 79% of organisations have experienced secrets leaks, with 77% of these incidents resulting in tangible damage, according to Ultimate Guide to NHIs.
• Only 5.7% of organisations have full visibility into their service accounts, which explains why NHI sprawl keeps outrunning manual oversight.
• For a broader baseline on machine identity exposure, see 52 NHI Breaches Analysis for recurring root-cause patterns and incident-level lessons.

What this signals

Identity blast radius: the right programme metric is no longer how many NHIs you have, but how much access each one can reach if compromised. That changes prioritisation from counting credentials to reducing the harm a single exposed token can cause.

With 97% of NHIs carrying excessive privileges in our research, the remediation backlog is structural rather than incidental, and it will not be solved by inventory alone. Security teams should expect governance pressure to shift toward entitlement reduction, ownership clarity, and offboarding automation.

Practitioners building out machine identity controls should align their operating model with the NIST Cybersecurity Framework 2.0 and the OWASP Non-Human Identity Top 10, because both reinforce the same direction of travel: discover, constrain, and verify machine access continuously.

For practitioners

• Build a continuous NHI inventory Track service accounts, API keys, OAuth tokens, secrets, bots, and AI agent credentials across code, CI/CD, cloud, and SaaS. Assign an owner and purpose to every credential so shadow identities do not remain unaccountable.
• Replace static bootstrap secrets Use native workload identity, cloud IAM roles, or Kubernetes service accounts to authenticate workloads before any secret is issued. That removes the weakest part of the trust chain and reduces reliance on shared secret zero patterns.
• Enforce ephemeral access for machine tasks Issue just-in-time credentials for narrowly scoped jobs and expire them automatically when the task completes. Long-lived machine secrets should be reserved for exceptional cases and reviewed as exceptions, not the default.
• Tighten privilege before exposure happens Review NHI permissions for unnecessary admin rights, cross-environment reach, and unused API scope. Focus remediation on reducing the identity blast radius so a leaked credential cannot become a broad access event.

Key takeaways

• The article’s core warning is that unmanaged NHIs have become a standing access problem, not just a discovery problem.
• Its evidence points to a scale issue, with machine identities multiplying far faster than human oversight can keep up.
• Practitioners should focus on lifecycle control, privilege reduction, and ephemeral access so exposed secrets do not become durable entry points.

Key terms

• Non-Human Identity: A non-human identity is any credentialed digital actor used by software, services, or automated processes instead of a person. It includes service accounts, API keys, OAuth tokens, certificates, secrets, bots, and AI agents that authenticate to systems and act on their own or on behalf of applications.
• Secret zero: Secret zero is the first trust problem in machine authentication: how a workload proves who it is before it can receive any credential at all. If that bootstrap step relies on a hardcoded password or shared secret, the entire identity chain inherits the same exposure and handling weaknesses.
• Identity blast radius: Identity blast radius is the amount of damage a compromised credential can cause based on its permissions, reach, and persistence. For NHIs, it is often the most useful risk measure because one leaked token can touch many systems before anyone notices or revokes it.
• Just-in-time access: Just-in-time access is a temporary access pattern that issues credentials only when a task needs them and removes them when the task ends. For machine identities, it reduces the value of exposed secrets and limits how long an attacker can reuse a credential if it is discovered.

What's in the full article

Akeyless's full blog post covers the operational detail this post intentionally leaves for the source:

• Product-specific comparison of discovery, rotation, and JIT access features across named NHI tools
• Detailed vendor descriptions of secretless authentication patterns using workload identities and cloud roles
• Feature-level discussion of behavioural guardrails, lifecycle automation, and policy enforcement in the platform
• Pricing and packaging notes for teams evaluating an NHI tooling purchase

👉 Akeyless's full post covers NHI tooling comparisons, lifecycle controls, and access governance details.

Deepen your knowledge

NHI governance, agentic AI identity, and machine identity security are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are responsible for identity security strategy or NHI governance in your organisation, it is worth exploring.