Non-human identities will dominate 2025 IAM planning

At a glance

What this is: This is Entro Security’s 2025 predictions piece, and its core finding is that NHI sprawl will force IAM teams to treat machine identities as a first-class governance problem.

Why it matters: It matters because service accounts, API keys, and cloud tokens sit inside the same access fabric as human identities, so weak NHI governance undermines IAM, PAM, and zero-trust programmes together.

By the numbers:

• Non-human identities are on track to outnumber human identities by 100 to 1 in enterprise environments.
• NHIs outnumber human identities by 25x to 50x in modern enterprises.
• 96% of organisations store secrets outside of secrets managers in vulnerable locations including code, config files, and CI/CD tools.

👉 Read Entro Security’s predictions on NHI takeover and 2025 identity risk

Context

Non-human identity sprawl is the security problem this article is really about. The source frames API keys, service accounts, and cloud tokens as the access layer that now underpins cloud operations, SaaS integrations, and development pipelines, but that layer is still managed as if it were a narrow exception rather than a core part of enterprise IAM.

The governance gap is that most programmes were built around human-centric assumptions: people are visible, offboarded, and reviewed on a schedule, while machine identities are created, reused, embedded, and forgotten across toolchains. That mismatch is why NHI lifecycle management, secrets rotation, and continuous inventory keep reappearing as the practical controls that matter.

As enterprises add more automation and cloud integration, the number of non-human identities grows faster than the control model around them. That makes zero trust, access reviews, and privileged access governance incomplete unless they explicitly include machine identities and the secrets they depend on.

Key questions

Q: How should security teams implement NHI lifecycle management?

A: Start with discovery, then assign every service account, API key, token, and certificate to an owner with a defined approval and revocation path. Lifecycle management only works when creation, rotation, offboarding, and exception handling are linked to a single governance process rather than spread across DevOps and security teams.

Q: Why do non-human identities complicate zero trust programmes?

A: Because NHIs authenticate at machine speed, often with long-lived secrets and repeated programmatic calls, which makes one-time trust decisions too weak. Zero trust for NHIs needs continuous verification, least privilege, and rapid revocation, otherwise the programme protects users better than it protects the automation layer.

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 you know if NHI governance is actually working?

A: Look for measurable reduction in unmanaged credentials, faster revocation after exposure, and clear ownership for each machine identity. If the organisation cannot prove where secrets live, who owns them, and how quickly they are invalidated, the governance model is still incomplete.

Technical breakdown

Why NHI lifecycle management is now an architecture problem

NHI lifecycle management is the discipline of discovering, provisioning, rotating, reviewing, and revoking machine identities across their full lifespan. In this article’s context, the issue is not just inventory, but the fact that NHIs are embedded in cloud operations, SaaS integrations, and CI/CD pipelines, where they can persist long after the service owner has changed. That creates hidden standing access. Good lifecycle architecture needs an authoritative source of identity inventory, tight creation controls, and clear offboarding paths for keys, tokens, and certificates.

Practical implication: Treat machine identity lifecycle as part of core IAM architecture, not an afterthought owned only by DevOps.

How AI changes secrets detection and NHI monitoring

The source argues that AI will be used to manage NHIs at scale because human-operated review cannot keep up with volume and churn. Technically, that means behavioural detection, unusual request patterns, and sequence analysis become more important than static allowlists. The risk is that AI is often positioned as a visibility layer when the real need is correlation across identity, context, and action. AI can help surface anomalies, but it does not replace ownership, revocation, or policy authority.

Practical implication: Use AI to prioritise anomalies in NHI activity, but keep revocation, approval, and accountability in the identity stack.

Zero trust for NHIs depends on continuous verification

Zero trust architecture for NHIs means the system never assumes a token, service account, or workload identity is inherently safe because it is internal. Each access decision should be tied to context, purpose, and least privilege, with continuous re-evaluation rather than one-time trust. In practice, this is harder for machine identities because they often authenticate programmatically and repeatedly, not interactively. That makes static entitlements and long-lived secrets incompatible with a real zero-trust posture.

Practical implication: If NHIs are part of the environment, zero trust must include continuous credential review and rapid secret rotation.

Threat narrative

Attacker objective: The objective is to turn one overlooked machine credential into broad access across cloud and application environments.

1. Entry occurs when exposed service accounts, API keys, or cloud tokens are discovered inside development pipelines, configuration files, or integrations.
2. Escalation happens when those machine identities carry excessive standing privilege, allowing an attacker to move from a single credential to broader cloud or SaaS access.
3. Impact follows when the abused NHI is used to reach data, infrastructure, or downstream services that trust the identity implicitly.

Breaches seen in the wild

• Dropbox Sign breach — compromised Dropbox Sign service account exposed API keys and OAuth tokens.
• Cisco DevHub NHI breach — IntelBroker exploited exposed Cisco credentials, API tokens and keys in DevHub.

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

NHI Mgmt Group analysis

NHI sprawl is no longer a niche visibility problem, it is an enterprise control-plane problem. Once API keys, service accounts, cloud tokens, and workload credentials outnumber human identities by large multiples, IAM has to govern a much larger and less observable population. The issue is not just growth, but dispersion across pipelines, integrations, and cloud platforms. Practitioners should treat machine identity inventory as a core security boundary, not a reporting exercise.

Secret sprawl creates trust debt that compounds faster than remediation can clear it. When credentials live in code, config files, chat systems, and CI/CD tools, the organisation inherits hidden privilege that can outlast the original use case. That is why discovery alone is insufficient. The field needs to treat every unmanaged secret as deferred breach exposure, and practitioners should assume the attack surface grows until lifecycle control is explicit.

Zero trust does not become real until it includes non-human identities. Human-centric access models still dominate many programmes, but they cannot fully describe programmatic authentication, service-to-service delegation, or machine reuse. The implication is that zero trust for the enterprise is incomplete unless machine identities are included in the same governance scope as people and privileged admins.

Continuous monitoring without automated revocation is a weak control pattern for NHIs. The article is right to point toward AI-assisted detection, but detection only matters if it is coupled to identity ownership and rapid invalidation paths. In the broader market, this signals that visibility-centric NHI tools will keep colliding with operational reality unless they connect to credential lifecycle governance. Practitioners should re-evaluate whether they are measuring exposure or actually reducing it.

Lifecycle governance is the named concept the market keeps underestimating. In machine identity programmes, the real failure is not discovery alone but the absence of a disciplined path from creation to rotation to offboarding. That is the assumption many programmes still violate. The practitioner conclusion is simple: if you cannot prove the lifecycle of a secret or service account, you do not govern it.

From our research:

• 96% of organisations store secrets outside of secrets managers in vulnerable locations including code, config files, and CI/CD tools, according to The State of Secrets Sprawl 2026.
• A separate finding shows that 79% of organisations have experienced secrets leaks, and 77% of those incidents resulted in tangible damage.
• For lifecycle control and offboarding patterns, see Ultimate Guide to NHIs for the broader governance model.

What this signals

Secret sprawl will continue to outrun programme maturity unless teams operationalise lifecycle control. With 96% of organisations already storing secrets outside secrets managers, the next practical step is not more policy language but better inventory, ownership, and revocation workflows. That means IAM teams need to decide where machine identity governance sits in their operating model, not just in their tooling stack.

The most exposed organisations will be those that treat detection as a finish line. If a secret can be found but not rapidly invalidated, the control still leaves a live attack path. For practitioners, the forward signal is clear: build identity processes that connect discovery to offboarding, and align them with the Ultimate Guide to NHIs and Top 10 NHI Issues.

Control-blind automation is the emerging risk pattern. As enterprises add more machine-driven workflows, the governance question becomes whether the organisation can still explain every live secret and every active service account. That is a lifecycle and accountability problem as much as a technical one, and it will keep surfacing in zero-trust and PAM programmes unless those teams coordinate on the same NHI inventory.

For practitioners

• Map every machine identity to an owner Require a named business or platform owner for each service account, API key, token, and certificate so identity sprawl can be triaged and revoked quickly when it is no longer needed.
• Inventory secrets outside approved vaults Scan code repositories, CI/CD tools, chat systems, and config files for long-lived credentials, then move them into controlled storage with clear rotation and revocation processes.
• Separate detection from remediation Use anomaly detection to identify unusual machine identity behaviour, but route every alert into a revocation or rotation workflow that can invalidate the credential before reuse.
• Extend zero trust to machine identities Apply continuous verification, least privilege, and contextual authorisation to non-human identities, then review where standing access still exists for service accounts and workload tokens.
• Review offboarding paths for non-human identities Test whether departed applications, retired pipelines, and decommissioned integrations still leave valid secrets behind, then close those paths as part of standard IAM offboarding.

Key takeaways

• Non-human identity growth is turning machine access into a core IAM problem, not a niche engineering issue.
• Secrets left outside controlled vaults create durable exposure, because discovery without revocation still leaves active attack paths.
• Practitioners need ownership, lifecycle control, and continuous verification if they want zero trust to cover NHIs as well as people.

Key terms

• Non-Human Identity: A non-human identity is any machine credential used by software rather than a person, such as a service account, API key, token, or certificate. In practice, these identities often authenticate at scale, live across cloud and pipeline environments, and require their own lifecycle controls.
• NHI Lifecycle Management: NHI lifecycle management is the process of discovering, creating, rotating, reviewing, and retiring machine identities over time. For autonomous or heavily automated environments, it must also account for hidden reuse, embedded credentials, and the fact that many secrets survive long after the system that created them changes.
• Secrets Sprawl: Secrets sprawl is the uncontrolled spread of credentials across code, collaboration tools, configuration files, and automation systems. It matters because every extra copy expands the number of places an attacker can find a live credential and makes revocation slower and less reliable.
• Zero Trust for NHIs: Zero trust for NHIs applies continuous verification and least privilege to machine identities rather than assuming internal automation is safe. The control goal is to make every credential prove context and purpose continuously, not just at issuance.

What's in the full article

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

• The specific 2025 prediction themes and the order Entro Security assigns to them across NHI growth, AI, IAM, lifecycle, and zero trust.
• The vendor's recommendations for CISOs on continuous discovery, automated lifecycle management, and anomaly detection.
• The article's own examples of how AI is expected to affect secrets usage patterns and access monitoring.
• The framing Entro Security uses for why these trends matter to enterprise security planning in 2025.

👉 Entro Security’s full post covers the 2025 prediction set, lifecycle recommendations, and zero-trust guidance for machine identities.

Deepen your knowledge

NHI lifecycle management, secrets rotation, and zero-trust controls are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are formalising machine identity governance from a similar starting point, it is worth exploring.