In the ASIST system, data on 86 917 abnormal events from 2017 to 2023 are collected as research objects, and an indicator system for abnormal events was established. To ensure the safety of aviation operations, accurate and reliable risk assessment models were developed to analyze abnormal events in depth, thereby achieving effective risk management. Firstly, the principle of catastrophe theory was introduced into the fuzzy inference system, which enables it to better handle complex issues and enhance the accuracy of evaluations. Then, a risk assessment model based on catastrophe theory and fuzzy inference system was developed to assess the risks of abnormal aviation events. Additionally, 56 cases with detailed background information records were selected for instance analysis, and compared with the cloud model, to verify the feasibility and accuracy of the model. Finally, relevant indicators were controlled using fuzzy methods, providing guidance for the safety management work of aviation operations.