Deception attacks are a big danger to the security and durability of multi-agent systems (MASs). This article introduces a new technique to tackle the problem of deception attacks in nonlinear multi-agent systems (NMASs). The system can be attacked through sensors and actuators, which may lead to incomplete system data transmission and render the system state inaccessible for control design. To overcome this challenge, a fuzzy state observer is constructed to estimate the system state after the attacks, and the fuzzy logic system (FLS) is used to handle unfamiliar nonlinearities. The Nussbaum function is proposed to deal with unknown control directions and reduces system complexity. In addition, considering that there are both cooperative and competitive relationships between agents, event-triggered bipartite consensus fuzzy security adaptive control is given to mitigate the effects of deception attacks and alleviate communication resources. A based-state-observer event-triggered bipartite consensus NMASs adaptive fuzzy security control is given to achieve asymptotic output consistency after the attacks. Using Lyapunov theory, it has been demonstrated that all signals within the closed-loop system remain bounded. Finally, the test simulations show that the suggested approach can maintain the security and stability of the system during deception attacks with minimal data and resources.