For unmanned surface vehicles (USVs) affected by input saturation, unknown dynamics, and external disturbances under replay attacks, this paper proposes an adaptive neural trajectory tracking control (ANNTC) against replay attacks under the design framework of vector backstepping. To effectively deal with the replay attack signals in the sensor-controller channel, the finite coverage principle, neural networks, and first-order filtering technology are introduced, thus the unavailable attack delay of velocity and its first derivative, as well as unknown dynamic of the USV are successfully solved respectively in the kinematics channel and the dynamics channel, respectively. At the same time, with the help of an auxiliary dynamic system, input saturation of the actuator is tackled. Further, utilizing the single-parameter technology, external environment perturbation is overcome. The relevant theory verifies that all the signals in the closed-loop system of the USV are bounded. The simulation and analysis results show that the proposed scheme is of good control performance.