GoKawiilResearchers demonstrate model-to-model weight-editing attack that corrupts factual answers
A research paper describes a controlled experiment in which one AI model acted as an 'editor' and directly altered another model's weights, causing it to give a false answer (naming Buenos Aires instead of Sydney as host of the 2000 Olympics). The authors call this 'weight-space misfolding'—a persistent change to a model's parameters that exceeds the authority granted for legitimate editing, distinct from a temporary prompt-based manipulation.The test was conducted on a small model and is not evidence of this occurring in deployed systems or spreading between models in the wild.