Secrets management is still failing on lifecycle control and visibility

At a glance

What this is: This is a practical guide to secrets management that argues lifecycle control, centralised visibility, and automated rotation are essential for protecting machine identities.

Why it matters: It matters because IAM, PAM, and NHI programmes fail when secrets remain scattered, long-lived, and poorly audited across cloud and DevOps workflows.

By the numbers:

• Only 44% of organisations are currently using a dedicated secrets management system.
• The average cost of IT downtime is approximately $5,600 per minute according to Gartner.
• Credential abuse was the most common initial access vector, accounting for 22% of all breaches.

👉 Read Akeyless' essential guide to secrets management and machine identities

Context

Secrets management is the discipline of controlling access to passwords, API keys, tokens, certificates, and encryption keys so machines and applications only use them when intended. In this article, Akeyless frames that problem through machine identities, where service accounts, containers, APIs, and automation all depend on credentials that are too often scattered, reused, or left standing long after they should be removed.

The governance issue is broader than vault storage. Most enterprise environments now span cloud, hybrid, DevOps, and serverless workflows, which means secret sprawl, fragmented rotation, and weak auditability quickly become identity problems as much as security problems. For teams running NHI programmes, secrets management is really about lifecycle control, privilege scope, and proving who or what used a secret, when, and why.

Key questions

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

A: They should treat secrets as lifecycle-managed identities, not just encrypted values. That means assigning ownership, reducing standing credentials, automating rotation, and verifying revocation across every environment where the secret is deployed. If the organisation cannot trace usage end to end, the control is incomplete, even if the vault itself is secure.

Q: Why do long-lived secrets create more risk than teams expect?

A: Long-lived secrets expand the time available for theft, reuse, and lateral movement. They also accumulate copy paths across code, pipelines, and configuration files, which makes revocation harder and audit evidence weaker. The longer the credential persists, the more likely it is to survive beyond the application, owner, or environment that created it.

Q: What breaks when secret rotation is not tied to application dependencies?

A: Rotation can silently disrupt services that still depend on stale values, or worse, leave shadow copies active in scripts and configs. The issue is not rotation itself but incomplete dependency awareness. Teams need to know where a secret is consumed before they can rotate it safely and prove that the old value is gone.

Q: How do organisations know if secrets management is actually working?

A: They should look for short credential lifetimes, complete ownership records, reliable revocation evidence, and audit logs that show where each secret was used. If a team cannot prove who can access a secret and where it is deployed, the programme is providing storage, not control.

Technical breakdown

Why secrets sprawl breaks centralised control

Secrets sprawl happens when credentials, tokens, and certificates are distributed across repositories, configuration files, pipelines, and multiple platforms instead of one governed control plane. That fragmentation weakens visibility, makes rotation inconsistent, and creates blind spots in audit trails. In practical terms, the organisation may know a secret exists but not where it is deployed, which service depends on it, or whether every copy has been revoked. The problem is structural: as machine identities multiply, the number of places a secret can leak or persist also multiplies.

Practical implication: inventory every secret source of truth and every downstream consumer before attempting rotation or offboarding.

How dynamic secrets change the access model

Dynamic secrets replace long-lived credentials with short-lived, task-scoped access that is created when needed and revoked after use. That shifts the security model from static possession to time-bounded authorisation, which reduces the attack window if a credential is exposed. The architectural value is not just shorter lifespan, but tighter linkage between identity, workload, and purpose. For machine-to-machine access, dynamic issuance also supports cleaner separation between provisioning, usage, and revocation, which is where many legacy secrets programmes fail.

Practical implication: prefer ephemeral issuance for workloads that do not need persistent credential reuse.

Why auditing and rotation have to be lifecycle controls

Rotation without lifecycle governance only moves secrets around. A secrets programme has to know when credentials are created, where they are used, how often they are refreshed, and when they should be destroyed or replaced. That is why audit trails, role-based enforcement, and revocation logic are part of the control, not add-ons. When this is missing, expired certificates, orphaned tokens, and unmanaged application credentials become operational failure points, not just security findings. The governance question is whether the organisation can actually prove control over secret lifecycle end to end.

Practical implication: treat rotation, audit, and revocation as one workflow rather than separate tasks.

Threat narrative

Attacker objective: The attacker’s objective is to use unmanaged secrets to move into systems and data that should have been out of reach.

1. Entry occurs when attackers obtain exposed credentials, tokens, or API keys from repositories, files, or other unmanaged locations.
2. Escalation follows when those standing secrets are reused across environments and grant access well beyond the original application need.
3. Impact comes from unauthorised access, data theft, or service disruption when expired or unmanaged secrets remain active.

Breaches seen in the wild

• Sisense breach — unauthorized GitLab access led to exfiltration of access tokens, API keys and certificates.
• IOS app secrets leakage report — iOS apps leaking hardcoded secrets and credentials endangering user privacy.

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

NHI Mgmt Group analysis

Secret lifecycle control is now a governance discipline, not a tooling feature. The article describes the familiar mechanics of rotation, vaulting, and access control, but the real issue is whether organisations can manage machine credentials as governed assets across their full lifecycle. When secrets exist in code, pipelines, and distributed workloads, the control problem becomes one of ownership, expiry, revocation, and evidence. Practitioners should treat secrets management as part of identity governance, not as an isolated security utility.

Standing secret exposure window: This is the failure mode the article exposes most clearly. Static secrets are designed for conditions where access can be granted once and tolerated for long periods, but that assumption breaks when machine identities move quickly across cloud, DevOps, and multi-environment workflows. The implication is that long-lived credentials create a persistent blast radius that is out of step with modern delivery speed.

Centralised vaulting does not solve unmanaged dependency chains by itself. A vault can store secrets, but it does not automatically solve the problem of where those secrets are copied, embedded, or inherited by applications and pipelines. That means governance has to extend beyond storage into deployment patterns, application dependency mapping, and revocation assurance. The practitioner conclusion is that visibility and lifecycle control matter more than the storage layer alone.

Machine identity governance and secrets governance are now the same conversation. The article repeatedly ties secrets to machine access, which is the correct framing. Once credentials are the control point for service accounts, APIs, and workloads, access decisions are really identity decisions, and lifecycle failures are really identity failures. Teams that separate the two will keep solving symptoms instead of the operating model.

The market is moving toward operational proof, not policy language. The vendor’s emphasis on automation, auditing, and least privilege reflects a broader industry shift: practitioners need evidence that secrets are rotated, revoked, and traced in practice. That pushes NHI programmes toward measurable control outcomes, especially where compliance, uptime, and cloud delivery all depend on the same credential estate. Security teams should judge programmes by proof of control, not by the size of the vault.

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.
• Only 44% of developers are reported to follow security best practices for secrets management, exposing a significant developer behaviour gap, according to The State of Secrets in AppSec.
• For lifecycle control and offboarding patterns, see NHI Lifecycle Management Guide for how provisioning, rotation, and revocation should work together.

What this signals

Standing credential exposure window: the real governance problem is not whether a vault exists, but how long a secret can survive after the application or workflow that created it has changed. When that window remains open for days or weeks, the organisation is managing persistence, not risk reduction.

Teams should expect secrets governance to converge with NHI lifecycle controls, because machine identities now span code, pipeline, and runtime boundaries. The programmes that win will prove ownership, dependency mapping, and revocation, not just encryption at rest.

If your environment still relies on manually managed credentials, the next maturity step is not another policy document. It is a measurable control model that ties secret creation, usage, rotation, and destruction to workload identity and deployment evidence.

For practitioners

• Map every secret to an owner and a workload Build an inventory that ties each secret to the application, service account, pipeline, or API that consumes it. Without that dependency map, rotation and revocation will leave hidden breakpoints or orphaned access paths.
• Replace standing credentials with short-lived issuance Use ephemeral credentials for workloads that can tolerate re-authentication, especially in CI/CD and containerised environments. The goal is to shorten the exposure window and reduce the value of a leaked secret.
• Bind rotation to revocation evidence Do not count a credential as protected until you can confirm the old value has been disabled everywhere it was used. Track revocation completion across repositories, runtime configs, and downstream integrations.
• Integrate secret controls into DevOps change flow Require secret injection, rotation, and expiry checks as part of deployment workflows rather than as separate operational tasks. That reduces manual handling and exposes failures before they reach production.

Key takeaways

• Secrets management fails when organisations confuse encrypted storage with governed lifecycle control across machine identities.
• The evidence points to a structural gap: leaks take weeks to remediate, while daily delivery workflows keep multiplying where secrets can hide.
• Teams should prioritise ownership, dependency mapping, and revocation proof before adding more vault layers or rotation policy language.

Key terms

• Secrets Management: Secrets management is the practice of storing, rotating, granting, and revoking sensitive credentials in a controlled way. In machine environments, it is a governance discipline as much as a security control, because access depends on how well the organisation can trace ownership, usage, expiry, and removal across systems.
• Machine Identity: A machine identity is the digital identity used by a non-human actor such as a service account, API, workload, container, or automated process. It needs clear ownership and lifecycle control because its credentials can be copied, reused, or left standing long after the original purpose has changed.
• Standing Credential: A standing credential is a secret or token that remains valid over an extended period instead of being issued only when needed. These credentials create persistent exposure because compromise can give an attacker repeated access until the secret is rotated, revoked, and removed from every place it was deployed.

What's in the full article

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

• Step-by-step explanations of how its secrets management model handles vaulting, dynamic secrets, and zero-knowledge key ownership.
• Direct comparisons of Akeyless with HashiCorp Vault, Azure Key Vault, Google Secret Manager, and AWS Secrets Manager.
• Implementation guidance for CI/CD injection, multi-cloud deployment, and operational rotation workflows.
• Vendor-specific examples of how its platform positions automation, scalability, and storage architecture for production use.

👉 Akeyless' full guide includes the vault model, lifecycle controls, and product comparison details.

Deepen your knowledge

NHI governance, machine identity security, and secrets management 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 lifecycle governance in your organisation, it is worth exploring.