This paper proposes a RiskRank method to analyze the network risk propagation by studying the the path and the law of the network risk propagation. By computing the similarity and proximity between network nodes, this work build a graph of network risk propagation which is used to train a network risk propagation model by iterations of random walk. The model is used to analyze the process of network risk propagation and evaluate the risk of network nodes. The high-risk clustering method is proposed by the density clustering algorithm to control the security situation by isolating the high-risk area.The experimental results show that the precision of the RiskRank model is 98.1 % and the recall of the RiskRank model is 86.4 %.