How should security teams use enterprise password management to reduce credential sprawl across applications, devices, and AI agents?

Security teams should treat enterprise password management as a control layer for credential discovery, storage, sharing, and access governance. The goal is to reduce password sprawl, limit exposed secrets, and extend protection to places traditional IAM and SSO do not fully cover. Strong adoption depends on policy alignment, user workflow fit, and clear ownership for sensitive access paths.

Why This Matters for Security Teams

enterprise password management is not just a user convenience control. It is one of the few practical ways to reduce credential sprawl across SaaS apps, legacy systems, shared admin accounts, endpoints, and now AI agents that can trigger login flows or consume stored secrets. When passwords, tokens, and recovery paths are left outside governance, the real risk is not only reuse but also uncontrolled sharing, weak ownership, and delayed revocation.

This is especially important because attackers increasingly target exposed credentials before defenders notice. NHIMG research on LLMjacking: How Attackers Hijack AI Using Compromised NHIs notes that when AWS credentials are exposed publicly, attackers attempt access within an average of 17 minutes and as quickly as 9 minutes in some cases. That speed means password sprawl is not a hygiene issue; it is an incident response issue. For broader governance, the NIST Cybersecurity Framework 2.0 reinforces that identity and access controls must be continuously managed, not assumed to be static.

In practice, many security teams discover their password problem only after a shared account, browser-saved secret, or agent workflow has already been abused.

How It Works in Practice

Effective enterprise password management reduces sprawl by making storage, sharing, and retrieval deliberate rather than incidental. The control works best when it becomes the default path for sensitive credentials, while SSO, PAM, and secrets management handle adjacent use cases. The key is to define what must live in the enterprise vault, who can request access, how approval works, and when access expires.

For human users, that usually means replacing informal sharing with role-scoped vault access, time-bound checkout, and audit logging. For applications and devices, it means cataloging every credential source, then moving long-lived secrets out of scripts, spreadsheets, and ticket notes into managed storage. For AI agents, the bar should be higher: current guidance suggests agents should not inherit broad human passwords at all. Instead, use workload identity, runtime authorization, and just-in-time credential issuance so the agent receives only the secret needed for a specific task.

• Inventory passwords, API keys, certificates, and recovery codes across applications, endpoints, and agent workflows.
• Classify which secrets require vault storage, shared checkout, break-glass access, or immediate retirement.
• Enforce MFA and approval for sensitive retrieval paths, especially for admin and production access.
• Use short-lived credentials for automation, and revoke them when the task completes.
• Log every access event so auditors can trace who, or what agent, retrieved which secret and why.

This approach aligns with the OWASP Non-Human Identity Top 10 and the agentic guidance in OWASP Agentic AI Top 10, both of which emphasize reducing exposed secrets and constraining non-human access paths. NHIMG’s Ultimate Guide to NHIs — Lifecycle Processes for Managing NHIs is also relevant because lifecycle discipline is what prevents forgotten credentials from becoming permanent exposure.

These controls tend to break down when organizations keep browser-stored passwords, local service accounts, and agent-issued tokens outside a single governance model because revocation and audit coverage fragment immediately.

Common Variations and Edge Cases

Tighter password governance often increases friction for developers, operators, and support teams, so organisations must balance stronger control against workflow speed and emergency access needs. That tradeoff is where many programs stall.

There is no universal standard for how enterprise password management should treat AI agents yet, but best practice is evolving quickly. Agents that perform narrow, repeatable tasks can sometimes use short-lived vault-issued secrets; agents with broader autonomy should rely more on workload identity and policy evaluation than on reusable passwords. The NIST AI Risk Management Framework and CSA MAESTRO agentic AI threat modeling framework both support this shift toward context-aware controls, even though implementation patterns still vary by platform.

Common edge cases include regulated break-glass accounts, inherited secrets in CI/CD pipelines, and devices that cannot support modern identity flows. In those environments, password management should be paired with compensating controls such as stronger monitoring, stricter TTLs, and explicit ownership. For AI-heavy environments, the research on AI Agents: The New Attack Surface report shows why this matters: many organizations already report agents acting outside intended scope, which makes reusable human passwords a poor fit for autonomous workflows.

Related resources from NHI Mgmt Group

• How should security teams implement policy controls for identities, applications, and devices in a business password management programme?
• How should security teams extend credential security across SaaS and AI environments at enterprise scale?
• How should security teams safely use AI agents to audit and apply identity changes across many applications?
• How should security teams use AI to reduce certification fatigue in access reviews?