Transportation networks belong to the class of critical infrastructure networks since a small deterioration in the service provision has the potential to cause considerable negative consequences on everyday activities. Among the reasons for the deterioration we can mention the shutdown of a subway station, the closure of one or more lanes on a bridge, the operation of an airport at a much reduced capacity. In order to measure the vulnerability of transportation network, it is necessary to determine the maximum possible disruption by assuming that there is an intelligent attacker wishing to give damage to the components of the network including the stations/stops and linkages. Identifying the worst disruptions can be realized by using interdiction models that are formulated by a bilevel mathematical programming model involving two decision makers: leader and follower. In this paper, we develop such a model referred to as attacker-operator model, where the leader is a virtual attacker who wants to cause the maximum possible disruption in the transportation network by minimizing the amount of flow among the nodes of the network, while the follower is the system operator who tries to reorganize the flow in the most effective way by maximizing the flow after the disruption. The benefit of such a model to the system operator is to determine the most vulnerable stations and linkages in the transportation network on one hand, and to take precautions in preventing the negative effects of the disruption on the other hand.