Framework built over TensorFlow implementing state-of-the-art Byzantine-resilient, distributed Stochastic Gradient Descent (SGD). Modular approach allows most of its components to be reused in other projects. Unreliable communication channels are supported, providing a performance speed-up over standard TensorFlow in saturated networks.