{"title":"基于主机的悬空域安全风险检测与度量","authors":"Mingming Zhang, Xiang Li, Baojun Liu, JianYu Lu, Yiming Zhang, Jianjun Chen, Haixin Duan, Shuang Hao, Xiaofeng Zheng","doi":"10.1145/3606376.3593534","DOIUrl":null,"url":null,"abstract":"Public hosting services offer a convenient and secure option for creating web applications. However, adversaries can take over a domain by exploiting released service endpoints, leading to hosting-based domain takeover. This threat has affected numerous popular websites, including the subdomains of microsoft.com. However, no effective detection system for identifying vulnerable domains at scale exists to date. This paper fills the research gap by presenting a novel framework, HostingChecker, for detecting domain takeovers. HostingChecker expands detection scope and improves efficiency compared to previous work by: (i) identifying vulnerable hosting services using a semi-automated method; and (ii) detecting vulnerable domains through passive reconstruction of domain dependency chains. The framework enables us to detect the subdomains of Tranco sites on a daily basis. It discovers 10,351 vulnerable subdomains under Tranco Top-1M apex domains, which is over 8× more than previous findings, demonstrating its effectiveness. Furthermore, we conduct an in-depth security analysis on the affected vendors (e.g., Amazon, Alibaba) and gain a suite of new insights, including flawed domain ownership validation implementation. In the end, we have reported the issues to the security response centers of affected vendors, and some (e.g., Baidu and Tencent) have adopted our mitigation. The full paper is provided in [2].","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"99 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Detecting and Measuring Security Risks of Hosting-Based Dangling Domains\",\"authors\":\"Mingming Zhang, Xiang Li, Baojun Liu, JianYu Lu, Yiming Zhang, Jianjun Chen, Haixin Duan, Shuang Hao, Xiaofeng Zheng\",\"doi\":\"10.1145/3606376.3593534\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Public hosting services offer a convenient and secure option for creating web applications. However, adversaries can take over a domain by exploiting released service endpoints, leading to hosting-based domain takeover. This threat has affected numerous popular websites, including the subdomains of microsoft.com. However, no effective detection system for identifying vulnerable domains at scale exists to date. This paper fills the research gap by presenting a novel framework, HostingChecker, for detecting domain takeovers. HostingChecker expands detection scope and improves efficiency compared to previous work by: (i) identifying vulnerable hosting services using a semi-automated method; and (ii) detecting vulnerable domains through passive reconstruction of domain dependency chains. The framework enables us to detect the subdomains of Tranco sites on a daily basis. It discovers 10,351 vulnerable subdomains under Tranco Top-1M apex domains, which is over 8× more than previous findings, demonstrating its effectiveness. Furthermore, we conduct an in-depth security analysis on the affected vendors (e.g., Amazon, Alibaba) and gain a suite of new insights, including flawed domain ownership validation implementation. In the end, we have reported the issues to the security response centers of affected vendors, and some (e.g., Baidu and Tencent) have adopted our mitigation. The full paper is provided in [2].\",\"PeriodicalId\":35745,\"journal\":{\"name\":\"Performance Evaluation Review\",\"volume\":\"99 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Performance Evaluation Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3606376.3593534\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Performance Evaluation Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3606376.3593534","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}
Detecting and Measuring Security Risks of Hosting-Based Dangling Domains
Public hosting services offer a convenient and secure option for creating web applications. However, adversaries can take over a domain by exploiting released service endpoints, leading to hosting-based domain takeover. This threat has affected numerous popular websites, including the subdomains of microsoft.com. However, no effective detection system for identifying vulnerable domains at scale exists to date. This paper fills the research gap by presenting a novel framework, HostingChecker, for detecting domain takeovers. HostingChecker expands detection scope and improves efficiency compared to previous work by: (i) identifying vulnerable hosting services using a semi-automated method; and (ii) detecting vulnerable domains through passive reconstruction of domain dependency chains. The framework enables us to detect the subdomains of Tranco sites on a daily basis. It discovers 10,351 vulnerable subdomains under Tranco Top-1M apex domains, which is over 8× more than previous findings, demonstrating its effectiveness. Furthermore, we conduct an in-depth security analysis on the affected vendors (e.g., Amazon, Alibaba) and gain a suite of new insights, including flawed domain ownership validation implementation. In the end, we have reported the issues to the security response centers of affected vendors, and some (e.g., Baidu and Tencent) have adopted our mitigation. The full paper is provided in [2].