The adversarial example attacks work against most known machine learning models, including statistical models, decision trees, feed-forward nets, convolutional nets, recurrent nets. They not only work against classifiers, but also against regression, and RL models.
TensorFlow supports weight quantization, but XNOR seems to be rewriting the trained model graph into a one that only uses binary boolean ops, and probably optimizing the graph along the way.
It's not the political opposition but the people who are on the other side. Looks like you used the biased sources of news. Let's just stop this for now, HN is not for politics.