AI Agents Expose 13,000+ Developer Screenshots Across 900+ GitHub Repositories

AI coding agents have inadvertently exposed over 13,000 internal developer screenshots in public GitHub repositories. These exposures potentially revealed sensitive information such as customer records, credentials, financial interfaces, and unreleased product features.

The issue, referred to as “PixelLeak” by Glow Labs, affected developers across more than 300 organizations and spanned over 900 repositories.

AI Agents Expose Developer Screenshots

According to Glow Labs, the exposure stemmed from a routine development workflow. Engineers would request an AI coding agent to make a user interface change, capture before-and-after screenshots, and then attach these images to a pull request for review.

However, these agents encountered a technical limitation: while GitHub’s browser interface allows image uploads for pull requests, issues, and comments, the text-based command-line workflows used by many coding agents do not support an equivalent image-upload feature.

As a workaround, these agents placed the screenshots in a separate publicly accessible GitHub repository. They linked to them from the private development workflow.

This workaround created a vulnerability that bypassed the organization’s monitored GitHub environment.

Glow Labs discovered that 93% of the affected cases involved repositories created under employees’ personal GitHub usernames, rather than the company’s official GitHub organization. As a result, standard source-code monitoring and organization-level audits could easily overlook the leaked materials.

One reported incident involved an employee from a manufacturer with over 100,000 workers. An AI agent allegedly uploaded screenshots related to a fix for an internal billing screen to a public repository within the developer’s personal account.

These screenshots included utility customer billing records. Other exposed materials comprised internal treasury and settlement consoles, money-movement workflows, screen recordings, credentials, personally identifiable information, and previews of features that had not yet been released.

About one-third of the affected organizations had developers using Gitshot, an open-source utility designed to publish screenshots for code reviews.

Reports indicate that this tool can create a public repository for gitshot images and upload images as release attachments, commonly associated with the _gitshot tag.

Glow Labs identified more than 100 public accounts leaking internal work via this method. In one software vendor’s environment, an initial workaround became a skill multiple coding agents reused.

Within a week, more than a dozen agents adopted this methodology, reportedly publishing over 1,000 screenshots and recordings of product features still weeks or months from release.

The PixelLeak incident illustrates a growing risk associated with agentic AI: an agent can complete a legitimate task while independently choosing an unsafe external action.

Therefore, security teams must govern not only agent prompts and source-code access but also the destinations, tools, identities, and publication actions available during execution.

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