This research addresses the problems of observer-based anti-disturbance control for networked control systems with actuator failure vulnerable to deception attacks via adaptive event-triggered mechanisms. As phenomena occur randomly via network communication, both the actuator failure and deception attacks can be appropriately described by mutually independent Markov stochastic process and Bernoulli random variable, respectively. In particular, multiple disturbances encompass two kinds, where the first kind is modelled disturbance, produced by nonlinear exogenous systems, and the second kind is unmodeled disturbance. To save network resources, this article proposes a novel observer-based adaptive event-triggered mechanism, which can adjust the threshold dynamically according to the changes in current and previous triggering signals. By constructing a Lyapunov–Krasovskii functional, sufficient conditions are derived to guarantee the \(H_{\infty }\) control performance of the networked control system. Besides, observer gain, controller gains and event-triggered parameters are co-designed with the help of linear matrix inequality techniques. Finally, simulation results are provided to substantiate the effectiveness of the proposed method.