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Sprint projectSep 14, 2026London, UK

What a Supervisor Would Ask: A Reusable Information Request for Frontier-Model Containment Failures, Applied to the OpenAI–Hugging Face Incident

Kassi V. Assamoi

Submitted to AI Incident Response Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

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Report: What a Supervisor Would Ask: A Reusable Information Request for Frontier-Model Containment Failures, Applied to the OpenAI–Hugging Face Incident

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The July 2026 OpenAI–Hugging Face incident is the first publicly documented autonomous breach of a third party by an AI system. Public accounts conflict on facts needed to assess compliance. This project drafts a supervisory instrument the EU AI Office could use to test those accounts against evidence: an information request under Article 91 of the AI Act.

The instrument combines a reusable template organised around event roles rather than dates, a case schedule applying it to the OpenAI events, and a cooperative information request to Hugging Face. Sections distinguish statutory obligations, Code of Practice commitments and proposed supervisory practice; questions specify answer formats and supporting evidence. A conditional comparison across the EU AI Act, the Code, California SB 53 and New York’s RAISE Act identifies what must be established before reporting deadlines can be calculated.

Drawn from prudential supervisory practice, the instrument is a prototype with a worked application to the public record. It has not yet been tested with a respondent.

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How much would this matter for AI safety if it worked? How innovative is it? For scores of 4-5: is this actually new to the field, or replicating recent work?

Scoring guide
  1. 1Negligible. No clear problem addressed, or no meaningful novelty.
  2. 2Limited. Addresses a real problem but with a generic or well-trodden approach. Incremental at best.
  3. 3Moderate. Clear problem with a reasonable approach; some novelty in framing or method beyond routine application of existing tools.
  4. 4Significant. Important problem with an original approach, or identifies a neglected problem area. A valuable contribution others could build on.
  5. 5Exceptional. Tackles a critical AI safety problem with a genuinely novel approach, or opens a new research direction. Clear theory of change. You'd be excited to share this with researchers in the area.

How sound are methodology, implementation, and findings?

Scoring guide
  1. 1Seriously flawed. Methodology broken, results uninterpretable, or implementation doesn't work.
  2. 2Weak. Approach has significant gaps: missing validation, flawed experimental design, or incomplete implementation.
  3. 3Competent. Technically solid given the short duration. Methodology makes sense, results are interpretable, limitations acknowledged, work builds toward clear conclusions.
  4. 4Strong. Thorough methodology with convincing validation. Results clearly support conclusions. Immediately useful for future work.
  5. 5Exceptional. Ambitious scope executed rigorously. Surprising findings, novel methods, or unusually robust validation.

How clearly are work, findings, and impact potential communicated?

Scoring guide
  1. 1Incomprehensible. Cannot determine what the project is actually claiming or doing.
  2. 2Hard to follow. Key information buried, missing, or diluted by excessive length. Significant effort to extract main points.
  3. 3Clear enough. Can understand the problem, approach, and results without undue effort. Core content clearly present: problem, method, findings, limitations.
  4. 4Well presented. Easy to follow, well-structured, appropriate level of detail. Target audience would get it quickly.
  5. 5Exceptionally clear. A pleasure to read. Complex ideas made accessible. Could serve as a model for how to present this type of work.

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Cite this project

@misc{assamoi2026supervisor,
  title = {{What a Supervisor Would Ask: A Reusable Information Request for Frontier-Model Containment Failures, Applied to the OpenAI–Hugging Face Incident}},
  author = {Kassi V. Assamoi},
  year = {2026},
  month = sep,
  note = {Submitted to AI Incident Response Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/what-a-supervisor-would-ask-a-reusable-information-request-for-frontiermodel-containment-failures-applied-to-the-openaihugging-face-incident-08nt}},
  url = {https://apartresearch.com/sprints/projects/what-a-supervisor-would-ask-a-reusable-information-request-for-frontiermodel-containment-failures-applied-to-the-openaihugging-face-incident-08nt}
}

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