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Disrupting a coordinated model-distillation campaign
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We recently identified and disrupted a coordinated campaign designed to extract protected reasoning from our models, with the earliest observed activity occurring in the first week of July. This activity is consistent with adversarial distillation: the systematic and unauthorized use of one model’s outputs or reasoning to help train, reproduce, or improve another model. Protected reasoning is the model’s internal record for working through a task; extracting it can reveal information withheld from the final answer and help others reproduce the model’s capabilities. The operators did not break our encryption,…




