NHI governance needs unified secrets and PAM controls at scale

At a glance

What this is: This is an analysis of how unified secrets management and PAM address the security gaps created by bot credentials and API identities at scale.

Why it matters: It matters because IAM, PAM, and IGA teams need a single governance model for non-human identities, not isolated vaulting or manual rotation workflows.

By the numbers:

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

👉 Read Securden's analysis of bot credentials and API identity security

Context

NHI governance fails when bot credentials, API keys, and service account privileges are managed as isolated technical artifacts instead of as identities with lifecycles. When credentials are hard-coded in code, embedded in pipeline variables, or spread across workstations, visibility breaks before monitoring or rotation can even begin.

The practical issue is not whether a secrets vault exists. It is whether the organisation can discover every non-human identity, assign least privilege, rotate credentials on policy, and revoke access when a bot, script, or service is retired. That is the control problem this article is trying to solve.

For teams building that model, the relevant baseline is the NHI lifecycle view in the NHI Lifecycle Management Guide, which maps provisioning, rotation, and offboarding into a single governance flow.

Key questions

Q: How should security teams govern service accounts and API keys across cloud platforms?

A: Treat them as lifecycle-managed identities, not static credentials. Centralise ownership, track where each identity is used, and require revocation paths for stale access. The goal is not just rotation, but visibility into who or what depends on each credential so decommissioning does not break production.

Q: Why do hardcoded secrets create such a large security risk?

A: Hardcoded secrets turn source code, build output, and configuration files into credential repositories, which makes exposure easy to repeat and difficult to contain. Once a secret is copied into multiple systems, revocation becomes slow and incomplete, and the attack window stays open far longer than most teams expect. That is why hardcoded credentials are a governance failure, not just a code smell.

Q: What do organisations get wrong about secrets management for non-human identities?

A: They often treat vaulting as if it solves identity assurance, when it really only stores the credential. The harder question is whether the workload is the right actor, at the right time, with the right scope. Without attestation and request-time policy, a vaulted secret still creates a reusable path to privilege.

Q: Who is accountable when credential compromise leads to lateral movement?

A: Accountability usually spans identity, endpoint, and application owners, because the failure is rarely a single control. Governance should assign ownership for credential assurance, privileged access scope, and revocation speed so that no one assumes the other team will contain the blast radius.

Technical breakdown

Why hard-coded secrets create a governance blind spot

Hard-coded API keys and plaintext credentials collapse the separation between code and identity. Once a secret is embedded in source code, config files, or CI/CD variables, it becomes copyable, reusable, and difficult to scope to a specific workload. That undermines least privilege because the credential often outlives the job it was meant to perform. In identity terms, the risk is not just exposure but persistence: a leaked secret can continue to function until it is found and revoked.

Practical implication: eliminate embedded credentials and make runtime retrieval the default for every non-human workload.

How unified secrets management changes NHI governance

A secrets vault centralises sensitive tokens, keys, and passwords so bots and applications fetch them at runtime rather than storing them in insecure places. The governance value is broader than storage. Centralisation creates a clear owner, a revocation point, and an auditable trail for every read and rotation event. When secrets management is tied to identity-aware policy, teams can distinguish between who may retrieve a secret, what workload may use it, and how long that access should exist.

Practical implication: treat the vault as a control point for lifecycle and audit, not just a repository for secrets.

Why PAM and just-in-time access matter for machine identities

Traditional PAM was built around elevated human access, but the same governance logic applies to service accounts and bots when they touch production systems. Just-in-time access reduces standing privilege, which limits the blast radius of a compromised credential. For machine identities, this means permissions should be issued for a task, observed centrally, and revoked automatically when the task ends. That model is strongest when paired with workload identity, signed tokens, or mTLS rather than static shared keys.

Practical implication: extend PAM policy to non-human identities that can reach production systems, not just to admins.

Threat narrative

Attacker objective: The attacker wants to reuse a trusted non-human credential to move through internal systems without tripping human MFA or session monitoring.

1. Entry occurs when attackers obtain hard-coded API keys, plaintext secrets, or embedded tokens from code repositories, configuration files, or developer endpoints.
2. Escalation follows when the stolen credential grants unattended access to production services, allowing the attacker to impersonate a trusted bot or microservice.
3. Impact occurs when the compromised identity is used for lateral movement, data exfiltration, or business logic abuse across internal APIs and downstream systems.

Breaches seen in the wild

• Reviewdog GitHub Action supply chain attack — reviewdog/action-setup GitHub Action supply chain attack exposed secrets.
• 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

Unified identity controls are now the baseline for NHI governance, not an optimisation. The article is directionally correct that secrets management and PAM cannot remain separate silos when bots, scripts, and APIs all use credentials to reach production. A vault without lifecycle control leaves privilege unresolved, while PAM without secrets governance leaves exposure unresolved. Practitioners should treat this as a single non-human identity control plane problem, not two adjacent tools.

Secret sprawl is the operating condition that breaks traditional governance assumptions. Hard-coded credentials in source code, pipeline variables, and developer workstations create a trust model where identity exists outside any reliable review cycle. That breaks the assumption that access can be discovered, attested, and removed through manual governance alone. The practitioner conclusion is that visibility and rotation must be designed into the identity model from the start.

Least privilege for non-human identities only works when the identity is treated as a lifecycle object. A bot or service account that is provisioned once and then left to persist will accumulate access just as a human user does, but with less oversight. The article’s lifecycle framing aligns with OWASP-NHI and NIST CSF principles because decommissioning is part of governance, not a cleanup task after compromise. Practitioners should measure machine identity lifecycle maturity, not just vault adoption.

Identity-aware API security depends on trustworthy upstream credentials. Behavioural detection and edge enforcement become more accurate when every API call is tied to a centrally managed, auditable non-human identity. Without that foundation, API security tools inherit noisy, ambiguous trust signals and spend their value compensating for identity drift. The implication is that API security and NHI governance should be designed as complementary control layers, not competing ones.

Top 10 NHI Issues: the article sits squarely inside the recurring NHI issues of secret sprawl, over-privilege, and lifecycle gaps. That makes it a governance story as much as a tooling story. The practical conclusion is that teams should map every bot and API credential to an owner, a policy, and a retirement path.

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.
• That is why the governance conversation keeps moving from storage to lifecycle, as explained in the Ultimate Guide to NHIs , Lifecycle Processes for Managing NHIs.

What this signals

Secret sprawl is the structural issue, not an edge case. When nearly half of organisations are still using dedicated secrets management, many programmes are effectively asking manual processes to govern machine identities at scale. The next maturity jump is not another vault feature, it is joining secrets, PAM, and lifecycle ownership into one control model.

The practical signal for IAM teams is that NHI governance will increasingly be judged by revocation speed, audit completeness, and ownership clarity rather than by how many credentials are stored. Teams that cannot trace a secret from creation to retirement will struggle to prove control, especially in hybrid and CI/CD-heavy environments.

For practitioners building that control model, the OWASP Non-Human Identity Top 10 remains a useful reference point for prioritising secret sprawl, over-privilege, and lifecycle gaps.

For practitioners

• Inventory every bot and API credential Create a complete register of secrets, service accounts, and workload identities across source code, pipelines, endpoints, and cloud platforms. Include ownership, environment, privilege scope, and retirement date so you can see which identities still matter and which are already orphaned.
• Centralise runtime secret retrieval Move credentials out of code and developer workstations into a managed vault so applications fetch them at runtime. Require application teams to use short-lived access paths rather than reusable static keys, especially for production databases and internal APIs.
• Enforce least privilege on machine identities Review every non-human account against its actual job function, then remove broad access that was granted for convenience. Use policy to distinguish read-only, task-scoped, and production-capable access so a single leaked credential cannot reach unrelated systems.
• Automate rotation and decommissioning Set rotation policy by credential criticality, then revoke access automatically when a bot, script, or service is retired. Tie decommissioning to lifecycle events so stale keys do not survive the workload they were issued for.
• Feed non-human identity events into SIEM and API monitoring Log every secret read, rotation, token issue, and privilege change into central monitoring. Correlate those events with API activity so anomalous use of a credential can be detected before it turns into data movement or service abuse.

Key takeaways

• Bot credentials become high-risk when they are hard-coded, long-lived, and detached from lifecycle governance.
• The evidence points to a persistent maturity gap, with many organisations still lacking dedicated secrets management and central oversight.
• IAM, PAM, and secrets management need to operate as one non-human identity control system if teams want to reduce blast radius.

Key terms

• Non-Human Identity: A non-human identity is any machine-based account or credential used by software, services, workloads, bots, or integrations to access systems. It must be governed as an identity with ownership, scope, rotation, and retirement, not treated as a static technical artifact.
• 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.
• PAM — Privileged Access Management: Solutions that control, monitor, and audit privileged access for both human and non-human identities. Traditional PAM tools are being extended to cover machine identities, service accounts, and agentic AI workloads.
• Workload Identity: The identity assigned to a software workload — such as a containerised application, serverless function, or microservice — enabling it to authenticate to other services without storing static credentials.

What's in the full article

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

• Platform-level comparison of vaulting, PAM, and lifecycle management across human and non-human identities
• Implementation checklist for runtime secret retrieval, rotation cadence, and decommissioning workflows
• Reference architecture showing how API gateways, SIEM, and machine identities fit together
• Feature comparison table covering deployment time, total cost of ownership, and scale

👉 Securden's full post covers the unified architecture, control comparison, and implementation checklist

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.