How should security teams find credentials on developer laptops?

Why This Matters for Security Teams

Developer laptops are one of the most common places where secrets escape policy because they sit at the boundary between sanctioned access and unmanaged workflow. Credentials often appear in shell history, local config files, IDE caches, browser storage, MCP configs, and AI tool artefacts long before they ever reach a central vault. That makes workstation discovery a governance problem, not just a malware hunting problem.

Teams that only scan repositories miss the messy reality of local development. A secret on disk may already be linked to a production API, a cloud account, or an NHI used by automation, which is why discovery has to be tied to ownership and access scope. NHIMG research on the Guide to the Secret Sprawl Challenge shows how quickly secrets proliferate when local workflows are not governed end to end. For baseline control expectations, the OWASP Non-Human Identity Top 10 is a useful reference point.

NHIMG’s 2024 Non-Human Identity Security Report found that 23.7% of organisations share secrets through insecure methods such as email or messaging applications. In practice, many security teams encounter workstation-based secret exposure only after a token has already been copied into a chat thread or reused in another tool, rather than through intentional discovery.

How It Works in Practice

Effective discovery starts with endpoint-local content collection, then moves to classification, ownership mapping, and response. The goal is to find credentials where developers actually work, not where policy assumes they work. That means scanning common local surfaces such as shell history, dotfiles, environment snapshots, cached CLI tokens, container tooling state, MCP configuration, and files created by AI assistants or code editors. The basic control logic aligns with NIST SP 800-63 Digital Identity Guidelines for identity assurance, and with NIST guidance on protecting secrets and access paths in NIST SP 800-53 Rev 5 Security and Privacy Controls.

A practical workflow usually includes:

• Scanning local files, hidden directories, and developer tool state that repository scanners do not see.
• Detecting credential patterns, token formats, certificate material, and configuration references to secret stores.
• Enriching findings with endpoint user, device, project, and workload ownership.
• Mapping each secret to the system or NHI it can reach, so the result is an access decision input.
• Revoking, rotating, or quarantining secrets with short TTLs when exposure is confirmed.

This is where static search alone breaks down. A secret in a local cache may be valid only for a build step, while another may be a long-lived API key with broad lateral reach. Current guidance suggests that teams should treat local discovery as part of secret lifecycle management, not as a one-time sweep. NHIMG’s Ultimate Guide to NHIs — Static vs Dynamic Secrets is especially relevant here. These controls tend to break down on unmanaged BYOD laptops and heavily customized developer environments because file paths, token stores, and assistant artefacts vary too widely for fixed signatures alone.

Common Variations and Edge Cases

Tighter local scanning often increases noise, endpoint load, and privacy review overhead, so organisations have to balance broader coverage against operational friction. That tradeoff is real when developers use multiple shells, ephemeral containers, remote IDEs, or offline workflows, because secrets may be duplicated across transient locations and then disappear before a central system can correlate them.

One important edge case is AI tooling. Prompts, model memory, MCP server configs, and plugin caches can carry live credentials or credential references, but best practice is still evolving and there is no universal standard for this yet. Security teams should focus on controlling what those tools can read, what they can store, and how quickly they can expire. Another common exception is when a secret is embedded in a legitimate test fixture or sample app. Those still require review, but response should consider blast radius, environment, and actual reach before triggering incident procedures.

For teams looking at the broader exposure pattern, NHIMG’s New York Times breach is a useful reminder that credential leakage often becomes visible only after multiple systems have already touched it. The safest operating model is to combine local discovery, ownership tagging, and rapid credential lifecycle action rather than treating every match as equal.

Related resources from NHI Mgmt Group

• How should security teams prioritise NHI remediation in cloud environments?
• How should security teams govern non-human identities at scale?
• How should security teams govern non-human identities for compliance?
• How should security teams govern non-human identities in Salesforce?