Identity security for every identity: what CyberArk’s message changes

At a glance

What this is: CyberArk argues that identity security must cover human, machine, and AI identities with privilege controls, governance, and lifecycle management.

Why it matters: That matters because IAM teams need one operating model for human access, non-human identity sprawl, and emerging AI identity risk, not separate programmes that leave gaps at the seams.

By the numbers:

• 87% of organizations have experienced at least two successful identity-related breaches.

👉 Read CyberArk's analysis of identity security across human, machine, and AI identities

Context

Identity security is the discipline of controlling who or what can access systems, data, and tools, and under what conditions. CyberArk's message is that the scope now spans workforce users, service accounts, machine identities, and AI identities, all of which can carry privilege and create breach pathways when governance is fragmented.

The governance gap is not just visibility. It is the assumption that one access model can safely cover identities with different lifecycles, different threat surfaces, and different privilege patterns. For IAM, PAM, and IGA teams, the practical question is how to enforce least privilege, review, rotation, and offboarding consistently across human and non-human estates.

That makes this a programme issue rather than a point tool issue. Organisations that still treat machine and AI identities as operational leftovers are likely to miss the control seams where compromise turns into lateral movement or policy drift.

Key questions

Q: How should security teams govern machine and AI identities in the same IAM programme?

A: Treat them as separate actor classes with shared governance patterns. Both need ownership, least privilege, lifecycle controls, and revocation discipline, but AI-connected identities also need tighter runtime oversight because their behaviour can change through delegated tools and sessions. A single governance model should unify inventory, access review, and offboarding while keeping control rules specific to each identity type.

Q: Why do service accounts and API keys increase breach risk when privilege is standing?

A: Standing privilege turns a stolen or forgotten identity into a persistent access path. Service accounts and API keys are often reused across systems, poorly reviewed, and slow to revoke, which makes lateral movement easier once an attacker reaches them. Risk falls when access is scoped to a task, rotated regularly, and removed as soon as the workload no longer needs it.

Q: What do IAM teams get wrong about visibility into non-human identities?

A: They often stop at discovery. Seeing service accounts, tokens, and workload identities is useful, but visibility alone does not tell you whether the identity is over-privileged, still needed, or properly offboarded. The control objective is not just to count identities, but to prove that each one has an owner, a purpose, and an expiry path.

Q: Should organisations apply the same access review process to human and non-human identities?

A: No. Human access reviews can work on periodic certification cycles, but non-human identities often change faster and need event-based review tied to deployment, rotation, or decommissioning. The better model is shared governance with different review mechanics, so the process matches how each identity class is created, used, and retired.

Technical breakdown

Why identity sprawl becomes a privilege-control problem

Identity sprawl is not simply a visibility issue. Once service accounts, API keys, certificates, workload identities, and AI-connected identities multiply across cloud and on-prem environments, the control challenge shifts to privilege containment. Discovery tells you what exists, but privilege controls determine what each identity can actually do. In practice, sprawl becomes dangerous when identities are created faster than access can be reviewed, scoped, rotated, or offboarded. The result is not just a larger inventory, but a larger attack surface with inconsistent enforcement across platforms and teams.

Practical implication: Map discovery to entitlement scope so every identity type has an enforceable privilege boundary.

How lifecycle management changes for machine and AI identities

Lifecycle management for non-human identities is not a copy of human joiner-mover-leaver logic. Machines are provisioned for workloads, rotated for secrets hygiene, and decommissioned when services end. AI identities add another layer because runtime behaviour can change as tools, prompts, or delegated access patterns change. That means lifecycle governance has to track not only creation and retirement, but also session scope, policy drift, and delegated trust. Access reviews alone do not solve this if the identity's useful life is measured in hours or minutes rather than months.

Practical implication: Tie provisioning, rotation, and offboarding to the actual runtime lifecycle of each identity class.

What adaptive privilege controls are trying to enforce

Adaptive privilege controls apply context, risk, and role complexity to decide how much access an identity should receive at a given moment. For human users, that often means session elevation, approval flows, or step-up checks. For non-human identities, the same idea is expressed through tightly scoped secrets, short-lived credentials, and policy enforcement around use rather than just issuance. The architectural point is that privilege should be dynamic enough to match task context, but still measurable and reviewable. Without that, organisations end up with static grants that outlive the job they were meant to support.

Practical implication: Use context-aware privilege boundaries rather than static grants wherever task scope is predictable.

Threat narrative

Attacker objective: The attacker aims to turn one abused identity into broader access that bypasses normal trust boundaries and governance controls.

1. Entry occurs when an attacker reaches an identity surface that was overexposed, weakly governed, or insufficiently scoped, such as a service account, token, or privileged session.
2. Escalation follows when that identity carries more privilege than its workload or operator needs, allowing the attacker to move laterally or deepen access without immediate friction.
3. Impact lands when the compromised identity becomes a path to sensitive data, critical systems, or trust relationships that were assumed to be isolated.

Breaches seen in the wild

• Cisco DevHub NHI breach — IntelBroker exploited exposed Cisco credentials, API tokens and keys in DevHub.
• ASP.NET machine keys RCE attack — 3,000+ exposed ASP.NET machine keys enabled remote code execution.

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

NHI Mgmt Group analysis

Identity security has become a cross-actor governance problem, not a tool category. The article's core claim is that workforce, machine, and AI identities now sit inside the same privilege ecosystem. That means the failure mode is not isolated misconfiguration but inconsistent governance across actor types. IAM, PAM, and IGA teams should read this as a warning that programme boundaries, not just product gaps, are now where exposure accumulates.

Privilege controls matter more when identities can multiply faster than teams can review them. Once machine and AI identities scale, static entitlement thinking breaks down because access is created, reused, and forgotten at different speeds. OWASP-NHI and Zero Trust both point to the same operational reality: discovery without enforcement only inventories the problem. Practitioners should treat uncontrolled privilege growth as a structural risk, not a cleanup task.

Lifecycle discipline is the real test of whether identity security is coherent. The article highlights onboarding, access review, and automation, but the deeper issue is whether the organisation can prove that identities are removed or narrowed when their purpose ends. That is especially important for service accounts and workload identities, where offboarding is often informal. The practical implication is that lifecycle governance must be measurable across every identity class.

Right level of privilege is a named concept here because broad identity coverage still fails if entitlements remain static. The article repeatedly returns to context, role complexity, and dynamic controls, which signals a shift away from one-time provisioning toward continuously shaped access. In NIST-CSF and OWASP-NHI terms, that is the difference between knowing an identity exists and constraining what it can do. Practitioners should treat privilege shaping as the centre of the operating model, not an add-on.

AI identity governance is converging with machine identity governance faster than most programmes are ready for. The article places AI alongside machine and workforce identities, which reflects a market reality: governance questions now span secrets, sessions, entitlements, and delegated execution. That convergence means teams can no longer separate 'AI security' from identity security. Practitioners should expect their IAM roadmap to absorb agentic and machine identity questions into the same control plane.

From our research:

• 80% of identity breaches involved compromised non-human identities such as service accounts and API keys, according to Ultimate Guide to NHIs.
• 91.6% of secrets remain valid five days after the targeted organisation is notified, showing a critical gap in remediation procedures.
• That persistence problem is explored further in 52 NHI Breaches Analysis, which shows how weak revocation discipline turns compromise into extended exposure.

What this signals

Identity security teams should expect programme boundaries to blur. As workforce, machine, and AI identities converge inside shared applications and cloud platforms, ownership and review models will need to become more granular rather than more centralised. The organisations that can separate actor type, privilege scope, and lifecycle state will be better positioned to absorb the next wave of identity-driven risk.

Right level of privilege will become the practical test of IAM maturity. Visibility, governance, and policy automation only matter if they change what an identity can do at runtime. That is why programmes should measure not just how many identities they can find, but how quickly they can narrow access when context changes.

Service account sprawl remains one of the easiest places to hide control debt. With only 5.7% of organisations having full visibility into their service accounts, the operational gap is still wide enough for stale access and undocumented ownership to persist. Teams should use the Ultimate Guide to NHIs as a reference point for inventory, ownership, and offboarding discipline.

For practitioners

• Inventory identities by actor type Separate workforce accounts, service accounts, workload identities, and AI-connected identities in your inventory so review cadence and ownership are not one-size-fits-all.
• Bind privilege to task scope Replace standing grants with task-scoped access where the workload or identity purpose is short-lived, and require a documented expiry condition for elevated rights.
• Automate offboarding for non-human identities Define revocation triggers for services, integrations, and credentials so decommissioned workloads do not retain usable access after their business purpose ends.
• Review machine and AI access together Use a single governance view for secrets, entitlements, and delegated execution so machine identities and AI identities are not managed in disconnected workflows.

Key takeaways

• CyberArk's message is that identity security can no longer stop at human users because machine and AI identities now sit inside the same privilege model.
• The strongest evidence in the article is the 87% breach figure, which reinforces that identity compromise is already a mainstream enterprise failure mode.
• For practitioners, the real work is aligning discovery, lifecycle management, and privilege controls so every identity class has clear ownership and expiry.

Key terms

• Non-Human Identity: A non-human identity is any machine- or software-based identity used to authenticate and access systems, data, or services. It includes service accounts, API keys, tokens, certificates, workload identities, and AI-connected identities that require ownership, lifecycle control, and revocation.
• Privilege Controls: Privilege controls are the mechanisms that limit what an identity can do after it is authenticated. In non-human environments, they include scoped credentials, session limits, entitlements, approval rules, and context-based enforcement that reduce the blast radius of compromise.
• Lifecycle Management: Lifecycle management is the process of creating, updating, reviewing, and removing identities as their purpose changes. For non-human identities, it must track workload creation, secret rotation, access reviews, and decommissioning so access does not outlive the system it was meant to support.
• Identity Sprawl: Identity sprawl is the uncontrolled growth of accounts, credentials, and access paths across systems and teams. It becomes a governance problem when owners, purposes, and expiry conditions are unclear, making it hard to prove that access is still needed or safely bounded.

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 programme maturity, it is worth exploring.

This post draws on content published by CyberArk: Identity security for every identity across human, machine, and AI. Read the original.