Modern distributed storage systems employ complex protocols to update replicated data. In this paper, we study whether such update protocols work correctly in the presence of correlated crashes. We find that the correctness of such protocols hinges on how local filesystem state is updated by each replica in the system. We build PACE, a framework that systematically generates and explores persistent states that can occur in a distributed execution. PACE uses a set of generic rules to effectively prune the state space, reducing checking time from days o hours in some cases. We apply PACE to eight widely used distributed storage systems to find correlated crash vulnerabilities, i.e., problems in the update protocol that lead to user-level guarantee violations. PACE finds a total of 26 vulnerabilities across eight systems, many of which lead to severe consequences such as data loss, corrupted data, or unavailable clusters.