With the popularity of Web applications, malicious webpages are increasingly harmful to users in the process of Web browsing. The malicious URL mentioned in this paper refers that the corresponding webpage contains malicious codes that are harmful to users. These malicious code exploits the vulnerabilities of browsers or plugins to attack users with download malware automatically. Based on the statistics and analysis of amounts of living malicious URL, and considering the anti-detection technologies being more used in malicious webpage such as the client environment detection and redirections, 25 features in three aspects are designed, namely, content of webpage, parameters of JavaScript function, and Web session flows. And a detection method-HADMW is proposed based on these 25 features and machine learning. The experimental results suggest that HADMW can achieve 96.2% accuracy and 94.6% recall rate, and it can detect malicious URL effectively. At the same time, compared with the detection results of open projects and security software, HADMW achieves better results.