As a company, it’s important to set up automated credential discovery against your documentation platform. The goal is simple: look for secrets in a place that should not contain secrets, validate what you find, and turn that visibility into action.
What you’ll learn in this post:
- How you can use Kingfisher, an open-source tool, to scan text and code-like content for exposed secrets.
- How credential validation helped us distinguish between:
- False positives
- Expired credentials
- Credentials that were still active and posed a real risk
What you can find
When you scan your environment, it’s possible that many credentials surface. Most would no longer be valid. But some still might. You might even find access-tokens belonging to an enterprise administrator or another role with specific privileges. I’m sure you can imagine the consequences if such tokens are misused: it could expose source code, alter repositories, change workflows, manage organization settings, access audit data, delete packages or repositories, and potentially affect security controls across your enterprise environment.
It is not just a password leak; it is a broad administrative capability accidentally made portable. That distinction matters. A leaked low-privilege credential is a problem. A leaked enterprise administrator token is a platform-level risk.
Why this matters
Secret scanning is often associated with source code repositories. But modern organizations do not work only in repositories. Knowledge is spread across collaboration tools, documentation systems, wikis, shared notes, internal portals, chat exports, and operational playbooks. These systems are designed for speed and knowledge sharing, which also makes them attractive places for accidental leakage.
The value of scanning these locations is visibility:
- Without visibility, an exposed credential can remain valid for months or years.
- With visibility, it can be assessed, invalidated, rotated, and used as a learning moment to improve the surrounding controls.
This is also relevant beyond the classic “external attacker” scenario. Insider risk is a real concern for large organizations, whether intentional or accidental. Recent public cases, such as allegations involving insider espionage in sensitive environments, show why companies take this seriously (while still respecting that allegations are not proof of guilt).
There is also a newer angle: AI agents.
As organizations connect agents to more tools, repositories, and operational systems, leaked credentials become even more important. An agent with access to internal content might discover a credential, reason about what it can do, and attempt to use it.
This is no longer a purely theoretical concern: examples such as OpenAI’s agent hacking its way into Hugging Face show how agentic systems can interact with real platforms in unexpected ways. That may happen because of malicious prompting, insecure tool design, excessive permissions, or unexpected autonomous behavior. The more capable our systems become, the more important it is to remove high-impact secrets from their reach.
Secret scanning is therefore not just cleanup. It is a guard rail for human workflows and agentic workflows alike.
What the scan looks like
From detection to guard rails.
The scan itself is only one part of the story. Detection tells you where the risk is. The real improvement comes from turning that signal into a repeatable control loop:
- Scan locations that should not contain secrets.
- Validate findings so teams can prioritize real exposure.
- Revoke or rotate credentials quickly.
- Review what access the credential had.
- Check audit logs for signs of misuse.
- Feed the lessons back into prevention and awareness.
Together, secret scanning and secret rotation create a more resilient pattern: find secrets earlier, make them less useful over time, and look for evidence of misuse.
The bigger lesson
The most important thing to remember is not that one credential can exist on one documentation page. The important thing to remember is that this class of exposure is discoverable, measurable, and reducible.
Organizations already invest heavily in protecting source code and production systems. Internal documentation deserves the same attention, because it often contains the operational memory of the organization: examples, commands, logs, decisions, and shortcuts. That makes it valuable, and sometimes risky.
By combining secret scanning, secret rotation, and audit log review you can move from reactive cleanup to continuous assurance. You can find what should not be there, reduce how long it remains useful, and check whether it was used in ways that deserve investigation.
That is a practical security improvement, and it is exactly the type of work your platform should be designed to support: not replacing human judgment, but giving teams better visibility, faster response, and stronger guard rails around the systems they already rely on. And we are here to help
Thibault
DevSecOps Lead
Proximus Ada