Identity security is now the frontline for cloud enterprises

At a glance

What this is: This is an analysis of why identity security has become the primary control plane for modern enterprises, with a focus on secrets sprawl, machine identities, and continuous access governance.

Why it matters: It matters because IAM, PAM, IGA, and NHI programmes now have to govern human and non-human access in the same operating environment, where leaked credentials can become immediate infrastructure exposure.

By the numbers:

• 69% of organizations have experienced an identity-related breach in the last three years.
• 39% of secrets exposed in public git repositories are for web application infrastructure, and 32% are for development CI/CD.

👉 Read Akeyless' analysis of identity security for modern cloud enterprises

Context

Identity security is the discipline of controlling who or what can access systems, data, and infrastructure. In this article, the core problem is that modern enterprises no longer fail at the network edge alone. They fail when credentials, secrets, and over-permissioned identities are exposed across cloud and software delivery environments, making identity security the real perimeter.

That shift matters for IAM, PAM, IGA, and NHI governance because the same access model now has to cover people, service accounts, workloads, and AI agents. Once secrets sprawl across repositories and cloud systems, a single leaked token or service account can become direct access to production systems rather than just a policy violation.

Key questions

Q: How should security teams reduce the risk from leaked secrets in cloud environments?

A: They should combine prevention, detection, and rapid revocation. That means scanning repositories and pipelines for exposed credentials, replacing long-lived secrets with temporary access where possible, and making sure every secret has a named owner and a tested rotation path. If a secret can survive a team change or deployment change, it is already a governance defect.

Q: Why do machine identities create more governance risk than most human accounts?

A: Machine identities often carry standing privileges, run continuously, and are embedded in systems that teams do not review as often as human access. If one of those identities is compromised, the attacker can inherit application-level trust rather than a single user session. That makes lifecycle control, ownership, and scope limitation essential for NHI programmes.

Q: What breaks when secrets are copied across repositories, pipelines, and cloud services?

A: Ownership, revocation, and visibility break first. The more places a secret is duplicated, the harder it becomes to know which systems still trust it and whether rotation has fully taken effect. That is why secrets sprawl becomes an access governance issue, not just an operational cleanup exercise.

Q: Who should be accountable when a leaked service account exposes production data?

A: Accountability should sit with the team that owns the workload, the platform team that governs its access path, and the security function that defines the review standard. If no one owns the lifecycle of the service account, the organisation has created an identity with privileges but no governance. That is the condition attackers exploit.

Technical breakdown

Why secrets sprawl turns identity into the attack surface

Secrets sprawl means credentials, API keys, tokens, and certificates are distributed across code repositories, build systems, cloud platforms, and automation tools without a single authoritative control point. The technical issue is not only exposure, but persistence. Once a secret is copied into multiple environments, rotation and revocation become fragmented, and access can continue even after the original use case has ended. That creates an identity control problem, not just a secrets hygiene problem, because the secret is functioning as the identity itself.

Practical implication: Map where secrets exist, who can retrieve them, and how revocation propagates across environments.

Machine identity security for service accounts and AI agents

Machine identities include service accounts, workloads, deployment pipelines, and AI agents that authenticate to systems without human intervention. They typically hold standing privileges because they must operate at runtime, which makes their compromise more valuable than a single user session. The challenge is that these identities often exist outside normal user-centric IAM assumptions, so access governance must cover discovery, privilege scope, and lifecycle events such as rotation and offboarding. Secretless authentication reduces exposure, but only if the surrounding trust model is actually enforced.

Practical implication: Treat machine identities as governed subjects with inventory, scope, and lifecycle controls rather than as technical endpoints.

Zero trust and contextual access for cloud workloads

Zero trust in cloud environments depends on contextual, temporary access rather than durable credentials stored inside workloads. Cloud-native patterns such as workload identity and federated tokens reduce the need for static secrets, but they do not eliminate authorisation risk. The architecture still needs strong policy enforcement, continuous verification, and auditability so access is constrained to the actual workload, environment, and purpose. If contextual access is not paired with lifecycle control, the environment simply moves from one type of standing privilege to another.

Practical implication: Use workload identity and federated access only where policy, monitoring, and revocation are equally mature.

Threat narrative

Attacker objective: The attacker aims to turn a leaked identity credential into durable access to cloud infrastructure, data stores, and operational systems.

1. Entry begins when attackers find exposed credentials or secrets in public repositories, developer tooling, or cloud-adjacent systems.
2. Escalation follows when a stolen API key, service account, or token grants broad access beyond the intended application boundary.
3. Impact occurs when the attacker uses that identity to reach infrastructure, databases, or customer data without triggering obvious perimeter controls.

Breaches seen in the wild

• 230M AWS environment compromise — 230M AWS environments compromised via exposed .env files with cloud credentials.
• MongoBleed breach — MongoBleed exposed secrets across 87K MongoDB servers.

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 the governing layer because the perimeter is now made of credentials, not walls. The article is right to place identity at the centre of defence, but the deeper point is that access control now determines whether cloud, DevOps, and machine-to-machine workflows remain governable. When secrets and privileges spread across repositories, pipelines, and workloads, traditional perimeter logic no longer describes where the attack surface begins. Practitioners should treat identity security as the control plane for the enterprise, not a supporting discipline.

Secrets sprawl is an identity governance problem before it is a tooling problem. A leaked key is not just an exposed secret, it is a portable identity that can be copied, reused, and abused outside the intended lifecycle. That makes inventory, ownership, rotation, and revocation central governance controls rather than back-office administration. The practical conclusion is that teams must know where each secret lives, who can still use it, and whether its privilege scope still matches the system it was created for.

Machine identity governance now spans service accounts, workloads, and AI agents, so the old human-first access model is incomplete. The article correctly includes non-human identities in its scope, and that matters because machine identities often hold broader and longer-lived privileges than human users. This is where NHI governance, PAM discipline, and lifecycle management converge. Organisations that still separate human access reviews from machine identity review are already operating with a blind spot that attackers can exploit.

Secretless architecture reduces exposure, but it does not replace lifecycle governance or contextual authorisation. Moving to federated or ephemeral access changes the shape of the problem, not the need for control. If policy enforcement, auditability, and revocation are weak, the environment still accumulates hidden trust paths, only now they are distributed across cloud trust relationships instead of stored secrets. Practitioners should assume that every simplification in credential storage must be matched by stronger governance over where trust is issued and how it expires.

Identity-related breach frequency confirms that access governance failures are already routine, not edge cases. With identity now carrying operational access for cloud and automation systems, the discipline has shifted from protecting login events to governing the full privilege lifecycle. That puts IAM, PAM, IGA, and NHI programmes on the same risk map. The field should stop treating identity incidents as isolated misconfigurations and start treating them as a structural control-plane failure.

From our research:

• The average estimated time to remediate a leaked secret is 27 days, despite 75% of organisations expressing strong confidence in their secrets management capabilities, according to The State of Secrets in AppSec.
• Organisations maintain an average of 6 distinct secrets manager instances, creating fragmentation that undermines centralised control, according to The State of Secrets in AppSec.
• For a broader control baseline, read Ultimate Guide to NHIs , Static vs Dynamic Secrets for the governance shift from durable credentials to temporary trust.

What this signals

Ephemeral access only reduces exposure if the surrounding governance model can still answer who owns the identity, where it is used, and when it should die. The enterprise signal here is that secretless and federated patterns are becoming table stakes, but they do not remove the need for lifecycle control. Teams that still rely on periodic reviews will miss identities whose value comes from runtime trust rather than static assignment.

With 43% of security professionals already concerned about AI systems learning and reproducing sensitive information patterns from codebases, the next control question is not just where secrets are stored, but how identity-aware pipelines prevent reuse of sensitive material from one workflow to another. That concern becomes more acute as AI-assisted development expands across cloud delivery chains.

For practitioners, the programme impact is clear: invest in inventory, ownership, and revocation paths that work across human, machine, and automation identities. The operating model should align with OWASP Non-Human Identity Top 10 and the NIST Cybersecurity Framework 2.0, because the control plane is now identity first.

For practitioners

• Inventory all secrets and machine identities continuously Build a current map of service accounts, API keys, tokens, certificates, and workload identities across code, CI/CD, cloud, and SaaS environments. Assign an owner and a retirement date to each identity so revocation is possible when the system or team changes.
• Move high-risk workloads to contextual, temporary access Replace durable secrets with federated or workload identity patterns where the platform can verify workload context at runtime. Ensure the access path still supports policy enforcement, logging, and emergency revocation when conditions change.
• Separate machine identity reviews from human access reviews Run distinct governance cadences for service accounts, workloads, and automation identities because their lifecycle, ownership, and privilege scope differ from human users. Use the review to confirm that standing privileges are still justified and that unused identities are removed.
• Harden public code and pipeline controls for secret exposure Scan repositories, build logs, and deployment workflows for exposed credentials, then enforce prevention controls that block secret commits and detect credential leakage early. Tie the response process to immediate rotation and dependency tracing so an exposed secret cannot remain active.

Key takeaways

• Identity security is now the primary control plane because attackers can exploit credentials and secrets without breaking the network perimeter.
• Secrets sprawl turns every copied token or key into a governance problem, since revocation and ownership become harder as distribution increases.
• Practitioners need unified lifecycle control for human and non-human identities, or cloud access will remain easier to inherit than to defend.

Key terms

• Secrets Sprawl: Secrets sprawl is the uncontrolled spread of credentials, tokens, API keys, and certificates across repositories, pipelines, cloud services, and endpoints. The risk is not only exposure, but persistence, because the same secret can remain trusted in multiple places after the original owner has forgotten it exists.
• Machine Identity: A machine identity is a non-human identity used by software, workloads, services, or automation to authenticate to other systems. In practice, it is the trust wrapper that allows one system to act as another, which makes its ownership, privilege scope, and lifecycle critical governance concerns.
• Secretless Authentication: Secretless authentication is a pattern that removes stored credentials from workloads and replaces them with ephemeral or federated trust mechanisms. It lowers exposure from stolen secrets, but it still requires policy enforcement, auditability, and revocation to prevent hidden trust paths from accumulating.
• Identity-Related Breach: An identity-related breach is an incident where stolen, abused, or over-permissioned identities are the main path to compromise. These events often bypass traditional perimeter defenses because the attacker is not breaking in technically, but logging in with a credential that the system still trusts.

What's in the full article

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

• A breakdown of identity security solution categories across IAM, PAM, secrets management, machine identity management, and IGA.
• Specific cloud integration examples, including AWS IRSA, GCP Workload Identity, and OIDC tokens, that show how the control model changes in practice.
• The vendor's checklist for evaluating centralised management, automated rotation, native cloud integrations, and compliance reporting.
• Practical guidance on secretless authentication and SaaS-based management for teams already past the strategy stage.

👉 The full Akeyless article covers cloud identity patterns, machine identity categories, and secrets management capabilities in more implementation detail.

Deepen your knowledge

NHI governance, agentic AI identity, and machine identity lifecycle 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.