Abstract: In response to the difficulty in identifying and evaluating high-risk scenarios of railway network data, this paper proposed a risk assessment method for high-risk scenarios of railway network data based on multiple-round consultation feedback. It quantified data weight, probability of safety risk occurrence, and safety risk loss by combining fault tree analysis and multi-round consultation feedback mechanism. Based on the quantified results, the paper identified differentiated risks, calculated risk values, and determined risk levels, and based on a simulation system, it conducted evaluation experiments. The experimental results show that this method can conduct risk assessment at two levels: data and system, and provide risk level determination results, provide reference for the identification and evaluation of high-risk scenarios of railway network data.