A smart grid is a modern power network designed to monitor, manage, and optimise the flow of electricity. A cyber attack on such a critical system can disrupt services and pose significant risks to public safety and national infrastructure. Cyber attackers targeting critical infrastructures like smart grids often follow predictable patterns that can be modelled and analysed. Attack graphs reveal these potential multi-stage attack patterns, highlighting attacker reachability. However, due to the sheer number of paths and the large size of the graph, their analysis becomes computationally challenging. In this paper, a modular analysis of attack graphs is proposed to address this issue by decomposing the graphs into manageable clusters or communities. By representing each community as a single node, the complex graph is transformed into a high-level abstraction that is easier to interpret. Segregating large attack graphs into clusters enables efficient, time-bound analysis and ultimately aids in defense strategy formulation.