OpenAI, the company that turned ChatGPT into a household name, has reportedly been using a custom version of that same technology to hunt for employees suspected of leaking internal information. According to detailed accounts attributed to The Information, the tool sifted through staff communications to flag possible sources of leaks, even as chief executive Sam Altman publicly talked about cracking down on internal disclosures. Altman has framed leaks as a serious problem and has said he is at “war” with people inside the company who share confidential details without permission.
The Leak-Hunting Mechanism
According to a report relayed by WinBuzzer, OpenAI built a custom version of ChatGPT that was fed internal data to identify potential leakers. The system was described as analyzing Slack messages, emails, and internal documentation and then cross-referencing those materials with the content of leaks that had appeared outside the company. By comparing language, topics, and access patterns, the model was said to generate a ranked list of employees whose communications most closely matched the leaked material.
WinBuzzer attributed its core description of the system to The Information and said the custom ChatGPT did more than simple keyword searches. The report described an operational workflow in which the model looked at who had access to sensitive documents, matched that group against Slack and email conversations, and then highlighted overlaps with the leaked information. According to this account, the AI tool effectively automated what would otherwise have been a labor-intensive internal investigation, turning the company’s own productivity tools into a surveillance and triage system for potential leak probes.
OpenAI’s Broader War on Leaks
The reported deployment of a leak-hunting ChatGPT fits into a wider campaign by Sam Altman to clamp down on internal disclosures. In coverage of his public comments, Yahoo Finance reported that Altman has explicitly described himself as being at “war” with people inside OpenAI who leak information. That rhetoric has been presented as part of a broader effort to tighten confidentiality rules and signal to staff that sharing internal details with outsiders will be treated as a serious breach of trust.
Yahoo Finance linked that language to a recent run of leaks about internal decisions and strategy debates, which Altman has framed as harmful to the company. Within that context, the decision to use a custom ChatGPT to police internal channels looks less like a one-off experiment and more like a concrete tactic in an ongoing struggle over information control. The message to employees, as described in that coverage, is that leadership is prepared to use the company’s most advanced tools not only to build products, but also to monitor the internal flow of information.
Evidence from Internal Tools
The strongest public description of how the leak-hunting system actually behaved comes from reporting by the New York Post, which cited internal output from the tool. According to that account, the custom ChatGPT did not just flag suspicious messages in Slack or email, but produced concrete lists of employees who had access to the leaked information. The Post described the system as generating names based on who could see particular documents and how closely their communications matched the leaked content.
The same New York Post report aligned with the WinBuzzer description of a cross-referencing process that tied together internal documentation, Slack conversations, and email threads. In that telling, the AI’s role was to narrow the field of potential leakers by combining access logs with text analysis, then hand that narrowed list to human managers or investigators. While the reporting did not detail specific disciplinary outcomes, it framed the internal ChatGPT as a key component in OpenAI’s attempt to trace leaks back to identifiable individuals.
Ethical and Privacy Implications
Using an AI system to mine internal chats, emails, and documents for potential leakers raises obvious questions about privacy and workplace monitoring. Even if companies already reserve the right to review communications on corporate systems, building a dedicated model to scour Slack and email for signs of disloyalty goes further than routine logging. In this case, the reports suggest that the same type of language model that powers public-facing ChatGPT was turned inward to scrutinize how employees talk and what they share.
For a company that presents itself as a leader in responsible AI, that choice has particular resonance. The reported system illustrates how easily powerful models can be adapted for surveillance-style tasks inside organizations, and it highlights a tension between protecting trade secrets and respecting employee autonomy. Legal compliance around such monitoring will depend on jurisdiction and the specifics of staff agreements, and the available reporting does not resolve whether OpenAI’s approach has been tested in court. The ethical debate, however, goes beyond legality and into how AI companies apply their own technology to their workers.
Reactions and Broader Impact
The current reporting offers only limited visibility into how OpenAI employees have reacted to the leak-hunting tool. Neither WinBuzzer nor the New York Post described organized internal pushback, and there is no detailed public account of staff being formally disciplined as a direct result of the AI’s output. That absence of detail leaves open questions about whether the system has chilled internal discussion, prompted resignations, or simply faded into the background as another compliance mechanism.
Outside OpenAI, the story has resonated as a concrete example of how generative AI can be used to monitor workers, not just assist them. Commentators have pointed to the irony of an AI safety-focused company leaning on a custom ChatGPT to police its own staff, even as its leaders talk publicly about managing the societal risks of the technology. The coverage from outlets like WinBuzzer and the New York Post has also given other employers a glimpse of how AI-powered internal investigations might work, which could encourage similar experiments elsewhere.
What We Don’t Know Yet
Despite the detailed descriptions of how the custom ChatGPT was configured, key parts of the story remain opaque. The reports do not establish how often the system has been used, how many employees it has flagged, or how accurate its suspicions have turned out to be. There is no public data on false positives, nor on whether anyone identified by the model was later cleared by human reviewers. Without that information, it is hard to judge whether the leak-hunting tool functions more as a serious investigative instrument or as a deterrent signal to the workforce.
There are also open questions about how long OpenAI intends to keep using such a system and whether staff have been fully informed about the scope of monitoring. The accounts based on The Information, as relayed by Yahoo Finance and WinBuzzer, focus on the existence and capabilities of the custom model rather than long-term governance rules. Until more internal policies become public or additional reporting surfaces, many of the most pressing questions about consent, oversight, and redress for misidentified employees remain unanswered, and any firm conclusions about the program’s impact would be unverified based on available sources.
More from Morning Overview
*This article was researched with the help of AI, with human editors creating the final content.
