Enterprise secrets management is shifting beyond traditional vaults

At a glance

What this is: This is an analysis of enterprise secrets management and its limitations, with Akeyless arguing that vaultless, SaaS-based controls better fit multi-cloud, hybrid, and compliance-heavy environments.

Why it matters: It matters because IAM, PAM, and NHI programmes increasingly depend on how secrets are stored, rotated, injected, and audited across workloads, applications, and AI-enabled systems.

By the numbers:

• Only 44% of organisations are currently using a dedicated secrets management system.

👉 Read Akeyless's analysis of enterprise secrets management at scale

Context

Enterprise secrets management is the discipline of controlling API keys, certificates, passwords, tokens, and other credentials across applications, infrastructure, and services. The core problem is not whether secrets exist, but whether they are governed consistently as systems scale across cloud, hybrid, and on-prem environments, where manual processes quickly create exposure windows.

The article frames vault-based approaches as increasingly difficult to operate in distributed environments because they can add infrastructure burden, rotation friction, and recovery complexity. For IAM and NHI teams, the practical question is whether the control model can support lifecycle governance, zero standing privilege, and auditability without creating new operational bottlenecks.

Key questions

Q: How should security teams govern cloud secrets across DevOps and runtime systems?

A: Treat secrets as lifecycle-managed NHI credentials, not static configuration values. Assign ownership, scope every credential to a purpose, rotate it on exposure or expiry, and remove standing access wherever possible. The governance goal is to shrink the time and scope of usable access, especially in pipelines and cloud workloads.

Q: When does vaulting stop being enough for secrets management?

A: Vaulting stops being enough when the organisation cannot answer where secrets are copied, who owns them, and whether they are still valid after exposure or workload change. At that point, the problem is not storage but governance. The programme needs discovery, monitoring, rotation, and revocation to reduce real risk.

Q: When should teams prioritise zero standing privilege for machine identities?

A: Prioritise zero standing privilege when a credential can reach production systems, cloud control planes, or sensitive data stores. If the identity exists primarily to support automation, it should receive only the access needed for the task and lose it immediately after use.

Q: How should organisations evaluate secretless access for AI agents and workloads?

A: They should ask whether the authentication path removes portable secrets without breaking auditability, policy enforcement, or recovery. Secretless access is useful only if the trust chain is still explicit and accountable. If the design hides where identity comes from, it simply moves the risk instead of reducing it.

Technical breakdown

Why enterprise secrets sprawl breaks vault-centric control models

Traditional vaults centralise storage, but centralisation alone does not solve lifecycle control. In large estates, the harder problem is synchronising issuance, rotation, revocation, and audit across many consuming systems without creating a bottleneck or a manual exception path. When secrets are embedded in CI/CD, containers, and hybrid applications, a vault becomes only one control point in a wider trust chain. If the surrounding workflow still relies on long-lived credentials, the vault reduces exposure in storage but not necessarily in use. Practical implication: treat vaulting as one layer in the control stack, not the whole secrets governance model.

Practical implication: Map where secrets are consumed, not just where they are stored, and measure whether rotation and revocation actually reach downstream workloads.

How secretless access changes the identity boundary for NHI and AI workloads

Secretless access shifts the identity boundary away from shared credentials and toward ephemeral authentication. In practice, that means workloads and AI agents authenticate through governed identity exchanges instead of carrying reusable secrets that can be copied, leaked, or reused outside their intended session. This matters because machine identity and AI agent identity problems are often created by credential persistence, not by authentication failure alone. A secretless pattern can reduce distribution risk, but only if the issuing trust chain, authorization policy, and logging remain coherent across cloud and on-prem targets. Practical implication: evaluate whether your workload identity model can survive without portable secrets before you redesign access patterns.

Practical implication: Define the trust chain for workloads and agents first, then decide where secrets can be eliminated and where they remain unavoidable.

Why zero standing privilege depends on runtime secrets governance

Zero standing privilege only works when access is short-lived and purpose-bound. Automated rotation, just-in-time provisioning, and credential expiration are the mechanisms that prevent a secret from becoming durable access. The challenge is operational: many organisations still use rotation schedules that do not align with deployment cadence, service ownership, or offboarding. That mismatch creates a standing-access problem even when the tooling looks modern. For IAM and PAM teams, the control failure is usually not absence of policy but absence of enforceable lifecycle orchestration. Practical implication: align secret lifetime to task lifetime, not to administrative convenience.

Practical implication: Tie secret lifetime to the shortest viable work interval and verify that revocation happens before the credential outlives the task.

NHI Mgmt Group analysis

Enterprise secrets management is now an identity governance problem, not just a storage problem. The article correctly frames secrets as credentials that must be issued, rotated, audited, and retired across applications and workloads. That means secrets management sits squarely inside IAM, PAM, and NHI governance, especially where service accounts and machine identities depend on those credentials. The practical conclusion is that teams should govern secrets as live identities with lifecycle state, not as static blobs in a vault.

Vault sprawl is not the same as secrets control. Centralising secrets in a vault can still leave organisations with inconsistent rotation, manual exception handling, and poor downstream enforcement. When developers, pipelines, containers, and applications all depend on the vault differently, the control plane becomes fragmented even if the storage layer is centralised. Practitioners should measure whether the whole lifecycle is governed end to end, not whether a vault exists.

Secretless access is the clearest signal that NHI governance is moving toward runtime trust decisions. The article’s focus on secretless access for machine identities and AI agents reflects a deeper shift away from portable credentials and toward ephemeral authorisation. That change matters because credential portability is a major source of blast radius. The practitioner takeaway is that identity architecture must now distinguish between stored secrets, runtime authentication, and delegated access.

Zero standing privilege is only credible when the credential lifetime is shorter than the operational review cycle. Automated rotation and just-in-time access make sense only if they are enforced consistently across cloud, hybrid, and on-prem workflows. If access reviews happen after the secret has already served its purpose, governance has arrived too late. The implication is that secrets policy must be tied to runtime enforcement, not annual assurance rituals.

From our research:

• 88% of security professionals are concerned about secrets sprawl, with 49% of those in larger organisations described as "very concerned", according to The 2024 State of Secrets Management Survey.
• 54% of organisations are dissatisfied with their current secrets management solution because not all secrets are secured, and 43% cite lack of central management.
• That governance gap is why the Guide to the Secret Sprawl Challenge is the natural next resource for teams trying to reduce exposure and operational drag.

What this signals

Secret sprawl is now a governance indicator, not a hygiene issue. When nearly nine in ten security professionals already worry about sprawl, the programme question becomes whether secrets ownership, rotation, and revocation are measurable across the estate. Teams should expect more scrutiny of runtime injection, workload identity, and offboarding because those are the places where secrets governance either holds or fails.

Vault consolidation will not be enough unless downstream consumption is also governed. A single control plane may simplify administration, but the operational risk sits where secrets are copied into delivery systems, containers, and applications. That is why lifecycle resources such as Ultimate Guide to NHIs , Lifecycle Processes for Managing NHIs matter as much as storage architecture.

The strongest programmes will increasingly pair secrets controls with workload identity standards and zero trust policy. Teams that already map machine credentials to OWASP Non-Human Identity Top 10 and NIST Cybersecurity Framework 2.0 will be better positioned to prove ownership, traceability, and revocation at scale.

For practitioners

• Inventory secrets by usage path Map every API key, certificate, password, and token to the application, pipeline, workload, or service account that consumes it. Separate storage location from actual usage so you can see where long-lived credentials create hidden dependency chains.
• Align rotation with workload lifecycle Set rotation and revocation rules based on deployment cadence, ownership changes, and offboarding events rather than static calendar intervals. Where workloads can tolerate it, move to short-lived credentials and ephemeral issuance instead of persistent shared secrets.
• Eliminate hardcoded secrets from delivery paths Block secrets in source control, CI/CD variables, build logs, and configuration files by using runtime injection and policy checks in the delivery pipeline. Make detection and revocation part of the same workflow so exposure is reduced before the secret can spread.
• Define who owns each secret lifecycle Assign accountable owners for issuance, rotation, revocation, and audit evidence for every secret class. Without explicit ownership, remediation delays turn into standing exposure, especially in multi-cloud and hybrid environments where teams assume someone else controls the secret.

Key takeaways

• Enterprise secrets management is failing when storage is centralised but lifecycle control remains fragmented.
• The main exposure is not just leaked credentials, but the operational delay in rotating, revoking, and proving control across distributed environments.
• The next governance step is to treat secrets as live identities and align their lifetime to workload behaviour, not to administrative convenience.

Key terms

• Secrets Management: The discipline of securely storing, distributing, rotating, and auditing secrets across an organisation's systems and pipelines — typically implemented via a centralised secrets vault such as HashiCorp Vault, AWS Secrets Manager, or Akeyless.
• Secretless Access: Secretless access is a pattern where workloads authenticate and receive access without relying on long-lived embedded credentials. It typically uses runtime identity verification, federation, and short-lived authorization decisions. The goal is to reduce exposure from hardcoded or reusable secrets while keeping machine-to-machine access functional.
• 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.
• 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.

What's in the full article

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

• Detailed feature breakdowns for vaultless deployment, distributed fragments cryptography, and gateway placement.
• Product-level explanations of secrets injection, runtime access paths, and multi-cloud integration patterns.
• Compliance and scalability claims tied to enterprise use cases such as Kubernetes, certificates, and password governance.
• Implementation-oriented descriptions of how the platform handles rotation, audit logging, and high availability at scale.

👉 Akeyless's full article covers the vaultless architecture, rotation model, and enterprise use cases in more 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.