At some point in the last few years, most of us made a series of very smart decisions. We automated everything we could. Onboarding, offboarding, role changes, cross-system integrations, data pipelines — if it was repetitive, we scripted it, connected it, or orchestrated it. And honestly? It was glorious. Our teams got faster, our error rates dropped, and we stopped doing the digital equivalent of manually carrying buckets between buildings.
What we didn’t fully reckon with is that every automation we built came with an identity attached.
Service accounts. API keys. OAuth tokens. Machine-to-machine credentials. Workflow runner credentials. Integration platform secrets. Every one of these is a non-human identity (NHI) — an entity that authenticates to your systems and performs actions, just like a user does, except it never gets locked out for too many failed attempts, never takes a security awareness training, and never gets offboarded when a project ends.
And here’s the uncomfortable math: in most organizations today, machine identities outnumber human identities by roughly 100 to 1. The even more uncomfortable part? Most security programs were designed for the 1%, not the 99.
Why This Is a Problem Right Now
NHIs aren’t new. Service accounts have existed since the dawn of enterprise IT. But several things have converged to make this a 2026 priority rather than a 2026 footnote:
The automation explosion. Tools like Okta Workflows, Workato, Zapier, and Make have democratized integration. Business users can now create automated workflows — and the credentials those workflows need — without IT being in the loop. That’s a feature and a threat surface simultaneously.
The AI agent wave. Every AI agent your organization deploys needs an identity to do anything useful. It needs to read your CRM, write to your ticketing system, query your database. Those are NHIs, and they’re being created faster than governance frameworks can keep up.
Attackers have noticed. The credential-based attacks that used to target user accounts are increasingly targeting machine identities, because they tend to be over-privileged, under-monitored, and permanent. A forgotten service account with admin rights is a gift to an attacker.
Compliance frameworks are catching up. NIST, SOC 2, and emerging frameworks are starting to ask hard questions about NHI governance. “We didn’t know we had that credential” is not an answer that auditors accept.
The Two Problems You Actually Need to Solve
Before looking at solutions, it helps to understand that NHI security is really two distinct problems that require different approaches — and confusing them is why many organizations end up with gaps even after buying tools.
Problem #1: Discovery and Governance You need to know what machine identities exist, what they can access, who owns them, and whether any of them are stale, over-privileged, or compromised. This is fundamentally a visibility and inventory problem.
Problem #2: Authentication and Enforcement You need to ensure that when a machine identity authenticates, it’s doing so securely — using short-lived credentials or modern auth protocols rather than long-lived static secrets — and that access is scoped appropriately. This is a policy and enforcement problem.
Most organizations need to address both. And that’s why no single tool solves this completely — at least not yet.
Where Okta Fits (And Where It Doesn’t)
If your organization uses Okta for identity, you already have some NHI capabilities, and they’re worth understanding before you go buy something else.
Okta’s core NHI strength is in managed, known identities within its ecosystem. Its machine-to-machine (M2M) authentication capabilities — built on OAuth 2.0 client credentials — let you register applications and services as OAuth clients, issue scoped access tokens, and enforce policy at authentication time. For service-to-service communication within your Okta-managed environment, this is genuinely solid.
Okta Workflows adds another layer: you can automate the lifecycle of service accounts and integrations, trigger deprovisioning when conditions are met, and build governance processes around identity events. If you’ve built your automation stack on top of Okta, you can extend that governance model to the machine identities Okta knows about.
The critical phrase there is “that Okta knows about.”
Here’s where Okta has a visibility gap: it doesn’t natively discover the OAuth tokens your SaaS applications have issued, the API keys your developers have generated and stored in Slack messages, the service account your finance team’s spreadsheet automation uses to query NetSuite, or the integration credential that’s been sitting in a config file since your last SaaS migration. Okta governs the identities that flow through Okta. It has limited visibility into the identities that don’t.
This isn’t a criticism — it’s just an architectural reality. Okta is an identity platform, not an NHI discovery engine. The two are complementary, not competing.
The Dedicated NHI Security Platforms
A new category of purpose-built NHI security tools has emerged to address the discovery and governance gap. They vary in approach, depth, and focus area — here’s how to think about the landscape:
Discovery-First Platforms
These tools start by crawling your environment — SaaS applications, cloud infrastructure, code repositories, and identity providers — to build a complete inventory of machine identities you didn’t know you had.
What they find: OAuth tokens, API keys, service accounts, secrets stored in configuration files, third-party app integrations, automation credentials, and certificates. The first time most organizations run one of these, the results are humbling. You will find credentials for applications that were decommissioned. You will find tokens with admin scope that were meant to be temporary. You will find things you genuinely cannot explain.
What to look for in this category: breadth of SaaS coverage (how many platforms can it see into?), depth of context (does it just list credentials, or does it tell you what each one can access?), and actionability (can you remediate from the platform, or does it just tell you what’s broken?).
Detection and Response Platforms
Some NHI tools go beyond inventory into behavioral monitoring — establishing a baseline of how each machine identity normally behaves and alerting when something deviates. Think of it as EDR, but for your bots. If a service account that normally reads from one database suddenly starts exfiltrating data at 2 AM, you want to know.
What to look for: quality of anomaly detection (low false positive rates matter a lot here — alert fatigue is real), speed of detection, and the quality of the response workflow.
Secretless / Workload Identity Platforms
A newer and architecturally bolder approach: instead of governing existing credentials, these tools help you eliminate long-lived credentials entirely. Rather than a service authenticating with an API key, it authenticates using a short-lived cryptographic proof of its identity — no secret to steal, no secret to rotate, no secret to accidentally commit to a GitHub repo.
This approach requires more architectural work to implement but represents the direction the industry is heading, especially for cloud-native environments. If you’re building new infrastructure, it’s worth understanding. If you’re managing legacy systems, it may not be practical in the near term.
Secrets Management Platforms
These tools focus specifically on the secure storage, rotation, and distribution of credentials — particularly for developer and DevOps workflows. If your engineering team is managing infrastructure secrets, database credentials, or CI/CD pipeline credentials, a dedicated secrets management platform can centralize and secure that sprawl.
This category overlaps with the broader NHI governance space but tends to be more developer-focused and infrastructure-centric. It’s a foundational layer, not a complete solution on its own.
How the Pieces Fit Together
A mature NHI security architecture looks something like this:
Layer 1 — Discover: A dedicated NHI discovery platform crawls your environment and builds a complete inventory. This feeds into your broader identity governance processes and gives you the ground truth about what exists.
Layer 2 — Govern: Your IAM platform (Okta, or equivalent) manages the identities that should exist — enforcing policy, managing lifecycle, and issuing scoped, time-limited credentials for known, authorized machine identities.
Layer 3 — Detect: Behavioral monitoring flags anomalies across both your known and discovered identities, giving you signal when something is behaving unexpectedly.
Layer 4 — Enforce: At the authentication layer, modern protocols (OAuth 2.0, OIDC, SPIFFE/SPIRE for workloads) replace static secrets wherever possible, reducing the blast radius of any single credential compromise.
Most organizations aren’t at Layer 4 yet. Most aren’t even fully at Layer 1. The good news is that the journey has a clear starting point.
Where to Actually Start
If your eyes are glazing over at the thought of implementing all of the above simultaneously, here’s the practical answer: start with inventory.
You cannot govern, detect, or enforce anything you don’t know about. Before you evaluate vendors, before you write policies, before you schedule a board briefing on NHI risk — go find out what you’re dealing with.
Step 1: Take inventory. Pull every service account from every system you manage. Document every API key your team has generated. Review OAuth connections in your major SaaS platforms (most have an admin view of connected applications). Look at your integration and automation platforms and list every credential they use. This process will be uncomfortable. Do it anyway.
Step 2: Assign a human owner to every non-human identity. This is where most organizations stall, because it’s not a technology problem — it’s a people and process problem. Every bot needs a person who is accountable for it. Someone who will notice when it’s doing something it shouldn’t. Someone who will clean it up when it’s no longer needed. Without this, your inventory becomes a list of orphans.
Step 3: Apply least privilege, actually. Audit what each machine identity can access. If it has admin rights “just in case,” that’s a conversation you need to have. Scope credentials to the minimum access required for their function. This step alone meaningfully reduces your risk.
Step 4: Build rotation and expiration into your process. Credentials that never expire will eventually be used against you — by an attacker, or by an auditor, or by both in that order. Establish expiration policies and rotation cadences before something forces you to.
Step 5: Then evaluate tooling. Once you understand your environment, you’ll be in a much better position to evaluate which tools fill your specific gaps — whether that’s discovery coverage, behavioral monitoring, secrets management, or secretless authentication. Tooling on top of chaos is just faster chaos.
The Bottom Line
The NHI problem is the natural consequence of building efficient, automated IT organizations. We created these identities deliberately, because they made us better at our jobs. Now the work is to govern them with the same rigor we apply to our human users.
Your employees have identity lifecycle management, access reviews, and offboarding checklists. Your service accounts deserve the same treatment — even if they’ll never complain about the process in an all-hands meeting.
The tooling is maturing. The frameworks are clarifying. The threat actors are not waiting.
Start with inventory. The rest follows.
