Definition
An Out-of-Distribution Attack defeats a classifier not by imitating the target class but by producing inputs so unlike anything in the training data that the model has no reliable basis for judgment. Against AI text detectors, this can mean generating text in an unusual register or era of prose the detector was never trained to recognize, causing it to misclassify confidently rather than uncertainly.