Face recognition systems are used in high security applications for identification, authentication and authorization. Being robust, is essential, not only towards Adversarial Examples, but also towards occluding accessories, such as facial masks, which become particularly relevant through the COVID19 pandemic. We have identified three inconspicuous facial areas to wear adversarial examples to attack face recognition. These are the mouth-nose section, the forehead and the eye area. In this paper, we will address the question of how much of a face needs to be present for successful identification and whether removing the identified critical regions is a viable countermeasure against adversarial examples.