Machine identity management is now central to NHI security

At a glance

What this is: The article argues that machine identity management is the control layer that keeps NHIs, secrets, and access lifecycles from becoming a breach and compliance problem.

Why it matters: It matters because IAM teams now have to govern machine identities with the same discipline they apply to people, while also accounting for cloud workloads, service accounts, and emerging AI-driven actors.

By the numbers:

• NHIs outnumber human identities by 25x to 50x in modern enterprises.
• Only 20% have formal processes for offboarding and revoking API keys, and even fewer have procedures for rotating them.
• 97% of NHIs carry excessive privileges, increasing unauthorised access and broadening the attack surface.

👉 Read Akeyless's analysis of machine identity management and NHI lifecycle controls

Context

Machine identity management is the discipline of issuing, provisioning, rotating, and revoking non-human credentials such as API keys, certificates, tokens, and service account access. The core problem is simple: organisations have invested far more in human identity controls than in the machine identities that increasingly move data, call services, and trigger automated workflows.

That gap matters across NHI, workload identity, and emerging agentic AI governance because a credential that is valid, over-scoped, or left behind can be reused long after its owner should have been offboarded. The article’s starting position is typical rather than exceptional, which is why this topic keeps resurfacing in identity programmes.

The article also makes the zero trust connection explicit. Once machines and services are treated as first-class identities, access decisions, audit trails, and lifecycle controls become identity governance problems rather than isolated DevOps tasks.

Key questions

Q: How should security teams govern machine identities differently from human users?

A: Security teams should govern machine identities with lifecycle, context, and runtime controls, not human approval workflows. That means separate ownership, purpose-based entitlement, expiry, and revocation for service accounts, bots, and agents. Human IAM can inform the model, but machine access needs faster review, tighter scoping, and automated enforcement.

Q: Why do NHIs create a different risk profile from human users?

A: NHIs often operate at scale, run continuously, and depend on secrets that are easy to copy, embed, or forget. Unlike human users, they can hold broad access without interactive friction, which makes privilege creep and credential reuse much more likely. That changes governance from session management to lifecycle and blast-radius control.

Q: What breaks when secrets are stored in code and CI/CD tools?

A: Access becomes invisible, reusable, and hard to revoke, which means the organisation loses control of where authentication material exists. Once secrets are embedded in code or pipeline tools, discovery gets harder, offboarding slows down, and the same credential can survive multiple deployment cycles.

Q: How do organisations reduce the impact of stolen API credentials?

A: Organisations reduce impact by shortening credential lifetime, removing credential reuse, and limiting each API identity to the smallest possible scope. They should also monitor for unusual usage patterns that suggest impersonation or automation abuse. If a credential is stolen, the organisation should be able to revoke it quickly without breaking unrelated services.

Technical breakdown

Why machine identity lifecycle management breaks at scale

Machine identity lifecycle management covers issuance, provisioning, rotation, and revocation for credentials used by workloads, services, and devices. The failure mode is not a single weak control. It is the combination of dynamic infrastructure, short deployment cycles, and manually managed secrets that outpace human review. If issuance is weak, an attacker can impersonate a trusted workload. If rotation is slow, the credential remains usable after exposure. If revocation is delayed, abandoned access stays live long enough to be abused.

Practical implication: treat lifecycle management as a continuous control plane, not a one-time provisioning task.

Secrets management, static credentials, and hidden access paths

Secrets are the operational bridge between an NHI and the systems it needs to reach. In practice, API keys, tokens, and certificates often end up in code, CI/CD pipelines, containers, or config files, which creates shadow access paths that are hard to inventory. Centralising secrets is useful, but centralisation alone does not solve the problem if credentials remain long-lived, overly privileged, or widely distributed. The technical issue is visibility plus persistence: once a secret is copied into multiple runtime contexts, revocation becomes slower and blast radius becomes harder to estimate.

Practical implication: inventory where secrets actually live at runtime, not just where policy says they should live.

Zero standing privilege for workloads and service accounts

Zero standing privilege removes always-on access and replaces it with time-bound or task-scoped permissions. For NHIs, this is especially important because service accounts and application identities rarely need persistent broad access, yet often receive it for convenience. RBAC helps group identities by function, but it can still leave broad permissions in place unless paired with tighter scoping and just-in-time patterns. The architectural goal is to make privilege temporary, observable, and revocable before it can be reused for lateral movement.

Practical implication: redesign high-risk workload access so credentials are issued only for the narrow task window they support.

Threat narrative

Attacker objective: The attacker aims to use compromised machine identities to move through cloud and application environments as a trusted workload and reach sensitive systems or data.

1. Entry occurs when exposed or embedded NHI credentials such as API keys, tokens, or certificates are discovered in code, pipelines, or public repositories.
2. Escalation follows when those credentials carry excessive privileges or remain valid long enough for an attacker to expand from the initial workload into adjacent systems.
3. Impact appears as data access, service abuse, or cloud environment compromise because the identity was trusted as a legitimate machine actor rather than a monitored exception.

Breaches seen in the wild

• Sisense breach — unauthorized GitLab access led to exfiltration of access tokens, API keys and certificates.
• IOS app secrets leakage report — iOS apps leaking hardcoded secrets and credentials endangering user privacy.

Read our 52 NHI Breaches Analysis report for a comprehensive view of breaches impacting Non-Human Identities including AI Agents.

NHI Mgmt Group analysis

Machine identity governance is now the baseline for modern IAM, not a specialist side track. The article correctly treats NHIs as first-class identities because they now outnumber human accounts and drive essential business workflows. That changes the governance burden for IAM, IGA, PAM, and cloud security teams alike. If machine credentials are not governed with the same lifecycle discipline as human access, identity programmes are incomplete by design.

Secrets sprawl is the named concept this article exposes. Secrets sprawl occurs when credentials are scattered across code, pipelines, runtime environments, and vault boundaries faster than governance can track them. The result is not just visibility loss, but accountability loss, because owners, revocation paths, and usage context drift apart. This is why the control problem is structural: practitioners must assume that every duplicated secret increases recovery complexity and attack persistence.

Zero trust for NHIs fails if privilege is still standing by default. The article’s RBAC and ZSP framing is directionally correct, but the deeper issue is that workload access is often provisioned for convenience and then left to persist. That violates the premise that machine access should be task-scoped and continuously re-justified. The practical conclusion is that zero trust cannot be layered on top of persistent machine privilege without redesigning the access model.

Machine identity management and agentic AI governance are converging faster than most programmes recognise. The article’s section on autonomous, agentic AI is the warning sign. Once software systems begin making runtime decisions and calling tools, the old assumption that access intent is known at provisioning time no longer holds. IAM teams should read this as a sign that NHI governance patterns will increasingly need to absorb autonomous behaviour, not just static workloads.

Auditability is now a lifecycle problem, not a logging problem. Compliance frameworks care about traceable access, but traceability fails when ownership, issuance, rotation, and revocation are not tied to a complete lifecycle record. Logging a credential use event is not enough if the credential should never have existed in that form or should already have been revoked. Practitioners need governance that proves who owns the machine identity at every stage.

From our research:

• Only 20% have formal processes for offboarding and revoking API keys, and even fewer have procedures for rotating them, according to Ultimate Guide to NHIs , Lifecycle Processes for Managing NHIs.
• Only 5.7% of organisations have full visibility into their service accounts, which means most teams still cannot see the full machine identity estate they are responsible for.
• That is why the 52 NHI Breaches Analysis remains a useful forward step for teams trying to connect lifecycle failure to real incident patterns.

What this signals

Machine identity governance will keep moving closer to core IAM operations as cloud estates, DevOps pipelines, and AI-driven services continue to expand. The teams that treat NHIs as an inventory problem will fall behind those that treat them as a lifecycle and privilege problem.

Secrets sprawl: the programme risk is no longer just that a secret leaks, but that no one can quickly prove where it exists, who owns it, and how to revoke it. That is a governance failure, not just a tooling gap.

With 97% of NHIs carrying excessive privileges in our research, the next maturity step is not simply better monitoring. It is a redesign of how non-human access is issued, scoped, and retired across the full identity lifecycle.

For practitioners

• Inventory all machine identities and their secret locations Map API keys, tokens, certificates, service accounts, and embedded secrets across code, CI/CD, containers, and cloud services. Include ownership, expiry, and revocation path so orphaned access can be removed without guesswork.
• Move high-risk NHIs to just-in-time access Replace always-on permissions with short-lived credentials for workloads that only need access during a defined task window. Align the workflow with Zero Standing Privilege so standing privilege is the exception, not the default.
• Automate rotation and revocation across the full lifecycle Tie issuance, renewal, and shutdown to automated workflows, and verify that applications can tolerate rotated secrets without downtime. Include emergency revocation for compromised credentials and orphaned service accounts.
• Integrate NHI controls into SIEM and CI/CD pipelines Send machine identity events into SIEM for anomaly detection and connect secrets handling to CI/CD so hardcoded credentials are blocked before deployment. Use the Ultimate Guide to NHIs for lifecycle context and the 52 NHI Breaches Analysis for real failure patterns.
• Review agentic AI access as part of NHI governance If AI systems can choose tools or trigger actions, classify their credentials and runtime permissions inside the same identity model used for NHIs. Use the OWASP NHI Top 10 to anchor risk reviews for those autonomous workflows.

Key takeaways

• Machine identities are already a primary governance problem because they scale faster than human identity controls.
• The biggest weakness is lifecycle failure, especially when secrets are embedded, over-privileged, or never revoked.
• Identity teams should respond by treating NHI inventory, rotation, and zero standing privilege as core programme controls.

Key terms

• Machine IAM: Machine IAM is the discipline of governing non-human identities such as APIs, service accounts, tokens, certificates, and automation workloads. It extends identity control to entities that authenticate programmatically and often operate continuously, which makes lifecycle management, revocation, and privilege scoping more important than login experience.
• Secrets Sprawl: The uncontrolled proliferation of sensitive credentials — API keys, tokens, passwords, certificates — across codebases, cloud environments, CI/CD pipelines, and configuration files. In 2024, over 50 million leaked secrets were found on the dark web.
• Zero Standing Privilege: A control model in which an identity does not keep persistent access unless it is actively needed. For NHIs, this means credentials and permissions are issued for a narrow task and then removed. It reduces the time window and reuse value of stolen access.
• Secretless Authentication: Secretless authentication is a pattern that keeps long-lived credentials out of application code and runtime memory wherever possible. Instead of exposing secrets directly to workloads, the access path mediates credential delivery at connection time, reducing the chance that stolen configuration or code reveals reusable access.

What's in the full article

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

• Step-by-step lifecycle examples for issuing, provisioning, rotating, and revoking machine identities in cloud environments
• Implementation guidance for embedding secrets into CI/CD pipelines without hardcoding or manual distribution
• Operational patterns for secretless authentication and runtime validation in ephemeral workloads
• Context on how Akeyless positions machine identity management alongside emerging agentic AI workloads

👉 The full Akeyless article covers lifecycle examples, secrets handling, and agentic AI considerations in more detail.

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 building or maturing an IAM programme, it is worth exploring.