This contribution presents an approach to improve the resilience of electricity distribution networks (DNs) to a class of cyber-physical failures by way of optimal allocation of distributed energy resources (DERs). The approach is motivated by the need to adapt the well-known security-constrained optimal power flow problem to DNs with remotely controllable (and, hence, vulnerable) distributed generation sources or loads. To this end, we model the interaction between the system operator (SO) and an external adversary as a three-stage sequential game. In this game, the SO allocates the available resources (Stage 0) and also responds to the adversary's action by optimally dispatching them (Stage 2). The adversary, on the other hand, compromises a subset of vulnerable components with the objective of inducing operating bound violations (Stage 1). We consider qualitatively different allocation strategies in Stage 0 and develop a scalable greedy heuristic to solve Stages 1–2 (i.e., bilevel optimization problem). We utilize this greedy heuristic to obtain structural insights about optimal adversarial compromises and desirable allocation strategies of the SO.