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Although deep networks have shown vulnerability to evasion attacks, suchattacks have usually unrealistic requirements. Recent literature discussed thepossibility to remove or not some of these requirements. This paper contributesto this literature by introducing a carpet-bombing patch attack which hasalmost no requirement. Targeting the feature representations, this patch attackdoes not require knowing the network task. This attack decreases accuracy onImagenet, mAP on Pascal Voc, and IoU on Cityscapes without being aware that theunderlying tasks involved classification, detection or semantic segmentation,respectively. Beyond the potential safety issues raised by this attack, theimpact of the carpet-bombing attack highlights some interesting property ofdeep network layer dynamic.

Carpet-bombing patch: attacking a deep network without usual requirements