Face recognition systems are used in high security applications for identification, authentication and authorization. Therefore they need to be robust not only to people wearing face accessories and masks like in the COVID19 pandemic, they also need to be robust against adversarial attacks. 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 critical regions is a viable countermeasure against adversarial examples.