  We evaluate the robustness of Adversarial Logit Pairing, a recently proposed
defense against adversarial examples. We find that a network trained with
Adversarial Logit Pairing achieves 0.6% accuracy in the threat model in which
the defense is considered. We provide a brief overview of the defense and the
threat models/claims considered, as well as a discussion of the methodology and
results of our attack, which may offer insights into the reasons underlying the
vulnerability of ALP to adversarial attack.
