<p>This article investigates the issue of robust adaptive fuzzy security constraint control for nonlinear multi-agent systems with input quantization and false data injection (FDI) attacks, which is used to tamper with false measurement signals transmitted by a communication network. Fuzzy logic systems are utilized to identify the unknown nonlinear dynamics, and a fuzzy state observer is constructed to identify unmeasurable states. Then the impact caused by the FDI attacks is addressed by utilizing an augmented approach to reconstruct the controlled system. With the help of barrier Lyapunov functions, the system states can be ensured do not beyond the constraint bounded. To avoid oscillations induced by the logarithmic quantizer, the hysteresis quantized input is realized and decomposed into two bounded nonlinear functions. Combining augmented approach and state observer, a robust adaptive fuzzy security state constraint output feedback control approach is proposed, which can ensure that all signals in the closed-loop system are semi-globally ultimately uniformly bounded, and the tracking error can converge to a smaller neighborhood containing the origin. Moreover, all states of the controlled system do not violate its pre-given bounded. Ultimately, the effectiveness of the proposed control scheme can be verified by the simulation.</p>