Much more robust than almost all modern ML algorithms which let's be real, aren't exactly applicable to anything outside recommendation systems and 2D image processing.
Meanwhile you have a whole separate discipline [1] for potential weaknesses on machine learning algorithms. Of course they may win when it comes to interdisciplinary ubiquity in CS, but any algorithm that relies on data assimilation and has little analytic formulation will suffer in robustness.
[1] https://en.wikipedia.org/wiki/Adversarial_machine_learning