I disagree. There is a huge amount of research on adversarially robust classifiers and detectors going on. One can also programmatically test a neural network on real data, synthetically damaged data, fully synthetic data, and adversarial data, and everything in between. You can statistically ensure you get any desired accuracy level on those tests. While that's not a hard proof of anything, it can allow you to be very confident in the nets abilities.