The localization of anomalous signals in wireless networks mainly depends on the analysis of individual parameters such as signal strength and propagation delay. Although the detection of abnormal signals can be realized to a certain extent, the localization accuracy and stability are low due to the lack of adaptability to complex environments. Therefore, this paper innovatively proposes an intelligent localization method for abnormal signals in wireless networks based on RSSI (Received Signal Strength Indicator) verification. The method digs deeper into the potential information of RSSI values, constructs a more accurate wireless signal propagation model, and skillfully combines the weight correction strategy to cope with the challenges of complex environments. The RSSI values of each node in the wireless network are collected and preprocessed, and the wireless signal propagation model is built based on the RSSI values to detect abnormal signal nodes. The distance values between known normal signal nodes and RSSI values are used to correct the weights between unknown abnormal signal nodes and each known normal signal node. According to the verified weight values, the position coordinates of the unknown abnormal signal nodes are obtained to realize the intelligent localization of abnormal signals in the wireless network. The experimental results show that the design method not only can effectively and accurately identify the abnormal signal nodes in the wireless network, but also has small node localization error and time consumption, and high localization accuracy.