The invention discloses a channel state information-based passive indoor positioning method. According to the method, ordinary equipment is utilized to build a data acquisition platform. The method specifically includes two stages, namely, an offline training stage and an online testing stage. According to the offline training stage, the channel state information data of each position where the body of a person is located, and the channel state information data are preprocessed, and then the preprocessed channel state information data are stored in a position fingerprint database, and a position-data fingerprint mapping relationship is established. According to the online testing stage, similarly, the data are preprocessed, a naive Bayes algorithm in machine learning is utilized to perform position classification. In order to further improve the accuracy of classification, a confidence method is introduced, and position misjudgment is decreased based on the classification result of a plurality of antenna pairs. With the method adopted, passive positioning of indoor people can be realized with low cost, and classification accuracy can achieve more than 90% under an optimal condition. The method of the invention has a certain application value in fields such as the intrusion detection field and the smart home field.