  In this work, we evaluate the adversarial robustness of BERT models trained
on German Hate Speech datasets. We also complement our evaluation with two
novel white-box character and word level attacks thereby contributing to the
range of attacks available. Furthermore, we also perform a comparison of two
novel character-level defense strategies and evaluate their robustness with one
another.
