In this paper, we propose a framework to study the resistance to bribery of nodes in a network via average consensus. We extend the proposed bribery resistance measure to sets of nodes, and networks. The proposed framework evaluates quantitatively how much an external entity needs to drive the state of an agent away from its current state, to change the final consensus value. Subsequently, we illustrate our framework with a set of examples, namely: i) how we can use it to compute the bribing resistance of each node in a network; ii) comparing our measure against metrics from the literature in measuring network bribing resistance; iii) how we may utilize the proposed framework to evaluate the bribing resistance of clusters/groups of nodes in large-scale networks.