Ruowen Wang, Ahmed M. Azab, W. Enck, Ninghui Li, P. Ning, Xun Chen, Wenbo Shen, Yueqiang Cheng
{"title":"SPOKE: Scalable Knowledge Collection and Attack Surface Analysis of Access Control Policy for Security Enhanced Android","authors":"Ruowen Wang, Ahmed M. Azab, W. Enck, Ninghui Li, P. Ning, Xun Chen, Wenbo Shen, Yueqiang Cheng","doi":"10.1145/3052973.3052991","DOIUrl":null,"url":null,"abstract":"SEAndroid is a mandatory access control (MAC) framework that can confine faulty applications on Android. Nevertheless, the effectiveness of SEAndroid enforcement depends on the employed policy. The growing complexity of Android makes it difficult for policy engineers to have complete domain knowledge on every system functionality. As a result, policy engineers sometimes craft over-permissive and ineffective policy rules, which unfortunately increased the attack surface of the Android system and have allowed multiple real-world privilege escalation attacks. We propose SPOKE, an SEAndroid Policy Knowledge Engine, that systematically extracts domain knowledge from rich-semantic functional tests and further uses the knowledge for characterizing the attack surface of SEAndroid policy rules. Our attack surface analysis is achieved by two steps: 1) It reveals policy rules that cannot be justified by the collected domain knowledge. 2) It identifies potentially over-permissive access patterns allowed by those unjustified rules as the attack surface. We evaluate SPOKE using 665 functional tests targeting 28 different categories of functionalities developed by Samsung Android Team. SPOKE successfully collected 12,491 access patterns for the 28 categories as domain knowledge, and used the knowledge to reveal 320 unjustified policy rules and 210 over-permissive access patterns defined by those rules, including one related to the notorious libstagefright vulnerability. These findings have been confirmed by policy engineers.","PeriodicalId":20540,"journal":{"name":"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3052973.3052991","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 29
Abstract
SEAndroid is a mandatory access control (MAC) framework that can confine faulty applications on Android. Nevertheless, the effectiveness of SEAndroid enforcement depends on the employed policy. The growing complexity of Android makes it difficult for policy engineers to have complete domain knowledge on every system functionality. As a result, policy engineers sometimes craft over-permissive and ineffective policy rules, which unfortunately increased the attack surface of the Android system and have allowed multiple real-world privilege escalation attacks. We propose SPOKE, an SEAndroid Policy Knowledge Engine, that systematically extracts domain knowledge from rich-semantic functional tests and further uses the knowledge for characterizing the attack surface of SEAndroid policy rules. Our attack surface analysis is achieved by two steps: 1) It reveals policy rules that cannot be justified by the collected domain knowledge. 2) It identifies potentially over-permissive access patterns allowed by those unjustified rules as the attack surface. We evaluate SPOKE using 665 functional tests targeting 28 different categories of functionalities developed by Samsung Android Team. SPOKE successfully collected 12,491 access patterns for the 28 categories as domain knowledge, and used the knowledge to reveal 320 unjustified policy rules and 210 over-permissive access patterns defined by those rules, including one related to the notorious libstagefright vulnerability. These findings have been confirmed by policy engineers.