This paper deals with the problem of fault detection for networked control systems with Markov transfer time delays, stochastic data drops, and sector-bounded nonlinearity. Two irrelevant Markov chains are employed to characterize the delays induced by the networks between the actuator–sensor and controller–actuator, respectively. Stochastic data drops distributed between actuators and sensors are modeled by random variables. The main tasks of this paper are the analysis and design of an $$H_\infty $$ H ∞ fault detection filter such that the filtering-error dynamics is stochastically stable with a prescribed $$H_\infty $$ H ∞ attenuation level for nonlinearity, transfer delays as well as data drops. Sufficient conditions for the existence of such a filter are presented in terms of linear matrix inequalities. Finally, two examples are included to show the efficiency of the proposed method.