Robust network flows are a concept for dealing with uncertainty and unforeseen failures in the network infrastructure. One of the most basic models is the Maximum Robust Flow problem: Given a network and an integer k, the task is to find a path flow of maximum robust value, i.e., the guaranteed value of surviving flow after removal of any k arcs in the network. The complexity of this problem appeared to have been settled a decade ago: Aneja et al. [1] showed that the problem can be solved efficiently when k = 1, while an article by Du and Chandrasekaran [2] established that the problem is NP -hard for any constant value of k larger than 1.We point to a flaw in the proof of the latter result, leaving the complexity for constant k open once again. For the case that k is not bounded by a constant, we present a new hardness proof, establishing NP -hardness even for instances where the number of paths is polynomial in the size of the network. We further show that computing optimal integral solutions is already NP -hard for k = 2 (whereas for k = 1, an efficient algorithm is known) and give a positive result for the case that capacities are in {1, 2}.