Secrets management is the control layer that makes zero trust work

At a glance

What this is: This is an analysis of how secrets management underpins zero trust architecture by governing credentials, authentication, and least-privilege access across human and machine interactions.

Why it matters: It matters because IAM, PAM, and NHI teams cannot make zero trust real if secrets remain long-lived, poorly governed, or invisible across workloads and service accounts.

By the numbers:

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

👉 Read Entro Security's analysis of secrets management in zero trust architecture

Context

Zero trust architecture depends on continuous verification, but that model breaks down if credentials are static, widely distributed, or difficult to rotate. In practice, secrets management becomes the enforcement layer for human-to-machine and machine-to-machine access, because identity alone is not enough when secrets are the real mechanism of trust.

For NHI programmes, the issue is not just whether a secret exists, but whether its lifecycle is governed tightly enough to support least privilege, auditing, and rapid revocation. The article’s core claim is that secrets management is not adjacent to zero trust architecture, it is one of the controls that makes the model operational.

That is why the same topic sits at the intersection of access control, workload identity, and privileged access governance. If secrets are unmanaged, zero trust becomes a monitoring philosophy instead of an enforceable identity model.

Key questions

Q: How should security teams govern secrets in zero trust environments?

A: Security teams should govern secrets as the credential layer that makes zero trust enforceable. That means inventorying every secret type, shortening lifetimes where possible, separating human and machine patterns, and revoking credentials when the trust relationship changes. If the secret remains static and reusable, zero trust becomes a policy statement rather than an access control model.

Q: Why do service account secrets create so much risk in zero trust architecture?

A: Service account secrets create risk because they often provide standing, non-interactive access to multiple systems. If one secret is leaked, reused, or over-scoped, attackers can move beyond the original application boundary without needing to defeat interactive authentication. In zero trust terms, the secret itself becomes the hidden trust anchor.

Q: What breaks when secrets are static instead of dynamic?

A: Static secrets break the assumption that access is temporary, contextual, and easy to revoke. They increase the blast radius of compromise, make change-based offboarding unreliable, and keep credentials valid long after the original task is complete. Dynamic secrets reduce that exposure by tying access more closely to time, purpose, and policy.

Q: Who should own secrets governance in a zero trust programme?

A: Ownership should sit across IAM, PAM, and platform teams, with clear accountability for issuance, rotation, revocation, and auditability. The control problem is cross-functional because secrets appear in infrastructure, applications, pipelines, and cloud services. If ownership is fragmented, the environment will accumulate standing access that zero trust cannot see.

Technical breakdown

Why secrets management is the enforcement point in zero trust architecture

Zero trust architecture assumes no implicit trust, but every system still needs a way to prove identity and obtain access. Secrets management supplies and governs those credentials, including passwords, API keys, tokens, and certificates, so that access can be issued only to the intended identity and only for the intended purpose. The technical dependency matters because identity policies alone do not secure the underlying secret, and a compromised secret bypasses policy intent. In NHI environments, this becomes the practical control plane for workload and service-account access.

Practical implication: treat secrets management as an access control dependency, not a vaulting side function.

Human-to-machine and machine-to-machine access need different secret lifecycles

Human-to-machine access usually involves interactive authentication, policy checks, and session-based verification, while machine-to-machine access relies on non-interactive credentials that often live longer and travel further. That creates different failure modes. Human credentials are more exposed to phishing and reuse, while machine secrets are more exposed to leakage in code, pipelines, and configuration stores. Zero trust only works across both patterns if the secret lifecycle matches the identity type, with strong issuance, revocation, and scope control.

Practical implication: separate human, workload, and service-account secret handling instead of applying one control pattern everywhere.

Least privilege and continuous verification fail when secrets are overbroad or static

Least privilege in zero trust is not just about role design. It also depends on how much authority each secret carries and how long it remains valid. Static secrets create standing access, which expands blast radius when leaked or reused. Dynamic secrets reduce that exposure by shortening the window of misuse and tying access more closely to policy and context. Without that, zero trust monitoring sees activity, but cannot meaningfully constrain the credential that enabled it.

Practical implication: reduce standing credential exposure by favoring short-lived, scoped secrets wherever the platform allows it.

Threat narrative

Attacker objective: The attacker wants to turn one compromised credential into broader access that bypasses zero trust assumptions and expands blast radius.

1. Entry occurs when attackers obtain exposed or reused credentials from code, pipelines, collaboration tools, or cloud configuration.
2. Escalation follows when the stolen secret carries standing privilege and can be used to access additional services or internal systems.
3. Impact lands as lateral movement, data access, or privileged misuse across the environment because the secret outlived its intended trust boundary.

Breaches seen in the wild

• MongoBleed breach — MongoBleed exposed secrets across 87K MongoDB servers.
• Shai Hulud npm malware campaign — Shai Hulud campaign: npm malware exposed secrets on GitHub.

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

NHI Mgmt Group analysis

Secrets management is the trust engine of zero trust architecture, not an accessory to it. Zero trust cannot be enforced if the credential layer is opaque, long-lived, or fragmented across teams and platforms. The article is right to connect IAM, PAM, and secrets, but the deeper point is that credential governance is where policy becomes operational reality. For practitioners, that means treating secret governance as a core control boundary in the zero trust programme.

Static secrets create standing privilege even when the access policy says otherwise. A password, API key, or certificate that remains valid across sessions undermines the assumption that every request is fresh and bounded. That is the failure mode zero trust is designed to eliminate, yet it persists whenever secrets are reused, embedded, or difficult to revoke. For security teams, the lesson is that effective zero trust requires the secret itself to have a narrow lifecycle, not just the policy around it.

Human authentication controls and machine identity controls cannot be collapsed into the same governance model. Human users can be challenged interactively, but machine identities usually cannot. That makes secret issuance, rotation, and revocation the primary governance mechanism for NHI access, while MFA and session controls remain relevant mainly for human entry points. For IAM and PAM teams, the implication is to segment governance by actor type instead of assuming one control stack fits all.

Identity blast radius is the real measure of secrets risk in a zero trust programme. The question is not only whether a secret is protected, but how far an attacker can move if it is exposed. Fragmented secrets managers, unmanaged service accounts, and over-scoped tokens all enlarge that blast radius. For practitioners, the priority is to map where one credential can still unlock many systems.

Static-vs-dynamic secrets: zero trust depends on whether the credential is reusable enough to outlive the trust decision that created it. Dynamic secrets fit the model because they compress exposure windows and make revocation meaningful. For practitioners, the challenge is to identify where standing credentials still act as hidden trust anchors in the environment.

From our research:

• Only 44% of organisations are currently using a dedicated secrets management system, 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.
• A stronger starting point is the Guide to the Secret Sprawl Challenge, which helps teams map where secrets live and why they evade governance.

What this signals

Static-vs-dynamic secrets: zero trust programmes should now be measured by how much standing credential exposure they still tolerate. If a token, certificate, or API key can outlive the business task it supports, the environment still depends on implicit trust even when policy language says otherwise.

Fragmentation is becoming the practical failure mode. With an average of 6 distinct secrets manager instances in use across organisations, central control is often diluted before the first rotation policy is written, which means IAM and PAM teams should prioritise consolidation and ownership clarity before adding more policy layers.

For practitioners

• Inventory every non-human credential path Map passwords, API keys, tokens, certificates, and service-account secrets across code, pipelines, cloud accounts, and collaboration tools. The goal is to identify where secrets exist outside the formal identity stack and where they create hidden standing access.
• Separate human and machine access policies Apply different issuance, validation, and revocation patterns for human users, workloads, and service accounts. Human access can rely on interactive assurance, but machine access needs lifecycle controls that assume non-interactive use and faster revocation.
• Shorten secret lifetime wherever possible Replace reusable static secrets with short-lived credentials for tasks that can tolerate dynamic issuance. This reduces the window between compromise and misuse, especially for build systems, automation accounts, and cloud-native workloads.
• Tie revocation to change events Trigger secret revocation when an application, pipeline, vendor relationship, or workload changes ownership or scope. Zero trust breaks when old credentials remain valid after the trust relationship has already changed.
• Measure blast radius by credential scope Review how many systems each secret can reach, how long it remains valid, and whether it can be reused outside the original task. Those three signals show whether secrets governance is actually reducing exposure or just documenting it.

Key takeaways

• Secrets management is the mechanism that makes zero trust enforceable across human and machine access.
• Static, reusable credentials expand blast radius and undermine the core assumptions of least privilege and continuous verification.
• IAM, PAM, and NHI teams should treat secret lifecycle control as a primary security objective, not a back-end hygiene task.

Key terms

• Secrets management: Secrets management is the controlled storage, issuance, rotation, and revocation of credentials such as passwords, tokens, API keys, and certificates. In NHI and workload environments, it is the mechanism that prevents credentials from becoming permanent trust anchors that outlive the access they were meant to enable.
• Zero trust architecture: Zero trust architecture is an operating model that assumes no implicit trust and requires each access decision to be verified. In practice, it depends on identity, policy, and credential governance working together so that access is continuously checked rather than granted once and left standing.
• Standing privilege: Standing privilege is access that remains valid beyond the immediate task or session. For human users it creates excess exposure, and for non-human identities it often becomes the default state of service accounts, API keys, and tokens unless lifecycle controls shorten or revoke that authority.
• Identity blast radius: Identity blast radius is the amount of systems, data, and actions that become reachable if one credential or account is compromised. It is a practical way to measure how far a leaked secret can move inside an environment and whether access design is actually limiting harm.

What's in the full article

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

• How the vendor positions secrets management across human-to-machine and machine-to-machine access patterns
• Examples of where secrets fit into zero trust architecture alongside IAM and PAM
• The article's operational framing for continuous validation and least privilege in practice
• The vendor's broader product context for scanning and contextual intelligence around discovered secrets

👉 The full Entro Security post expands on the role of secrets across IAM, PAM, and machine-to-machine access.

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 NHI governance in your organisation, it is worth exploring.