Paste-to-debug and prompt-layer risk

A pattern we see often in engineering teams:

An issue hits production. An engineer copies error logs, stack traces, snippets of code, configuration details, and pastes them into ChatGPT or Copilot to debug faster.

It works.

Those inputs often contain internal system structure, API endpoints, environment details, and sometimes credentials or tokens.

From a productivity perspective, it is efficient. From a security perspective, it is uncontrolled data exposure. This is not misuse in the traditional sense. It is normal behaviour, which is exactly what makes it difficult to manage.

Most organisations do not have visibility into this, let alone a way to enforce policy at the moment the prompt is sent.

AI has not created a brand-new risk category on its own. It has exposed an existing one at scale: sensitive operational context leaving your controlled systems through the browser, one paste at a time.

That is why we focus on the prompt layer: see what is being sent, align it to policy, and evidence it for security and compliance teams without pretending the tool will disappear from the workflow.