Tao Zheng;Qiyu Hou;Xingshu Chen;Hao Ren;Meng Li;Hongwei Li;Changxiang Shen
{"title":"Gupacker: Android恶意软件的通用解包框架","authors":"Tao Zheng;Qiyu Hou;Xingshu Chen;Hao Ren;Meng Li;Hongwei Li;Changxiang Shen","doi":"10.1109/TIFS.2025.3558592","DOIUrl":null,"url":null,"abstract":"Android malware authors often use packers to evade analysis. Although many unpacking tools have been proposed, they face two significant challenges: 1) They are easily impeded by anti-analysis techniques employed by packers, preventing efficient collection of hidden Dex data. 2) They are typically designed to unpack a specific packer and cannot handle malware packed with mixed packers. Consequently, many packed malware samples evade detection. To bridge this gap, we propose <inline-formula> <tex-math>$\\textsf {Gupacker}$ </tex-math></inline-formula>, a novel generalized unpacking framework. <inline-formula> <tex-math>$\\textsf {Gupacker}$ </tex-math></inline-formula> offers a generic solution for first-generation holistic packer by customizing the Android system source code. It identifies the type of packer and selects an appropriate unpacking function, constructs a deeper active call chain to achieve generic unpacking of second-generation function extraction packers, and uses JNI function and instruction monitoring to handle third-generation virtual obfuscation packer. On this basis, we counteract a diverse array of anti-analysis techniques. We conduct extensive experiments on 5K packed Android malware samples, comparing <inline-formula> <tex-math>$\\textsf {Gupacker}$ </tex-math></inline-formula> with 2 commercial and 4 state-of-the-art academic unpacking tools. The results demonstrate that <inline-formula> <tex-math>$\\textsf {Gupacker}$ </tex-math></inline-formula> significantly improves the efficiency of Android malware unpacking with acceptable system overhead. We analyze real packed applications based on <inline-formula> <tex-math>$\\textsf {Gupacker}$ </tex-math></inline-formula> and found several are second-packed by attackers, including WPS for Android, with tens of millions of users. We receive and responsibly report 13 0day vulnerabilities and also assist in the remediation of all vulnerabilities.","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"20 ","pages":"4338-4352"},"PeriodicalIF":6.3000,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Gupacker: Generalized Unpacking Framework for Android Malware\",\"authors\":\"Tao Zheng;Qiyu Hou;Xingshu Chen;Hao Ren;Meng Li;Hongwei Li;Changxiang Shen\",\"doi\":\"10.1109/TIFS.2025.3558592\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Android malware authors often use packers to evade analysis. Although many unpacking tools have been proposed, they face two significant challenges: 1) They are easily impeded by anti-analysis techniques employed by packers, preventing efficient collection of hidden Dex data. 2) They are typically designed to unpack a specific packer and cannot handle malware packed with mixed packers. Consequently, many packed malware samples evade detection. To bridge this gap, we propose <inline-formula> <tex-math>$\\\\textsf {Gupacker}$ </tex-math></inline-formula>, a novel generalized unpacking framework. <inline-formula> <tex-math>$\\\\textsf {Gupacker}$ </tex-math></inline-formula> offers a generic solution for first-generation holistic packer by customizing the Android system source code. It identifies the type of packer and selects an appropriate unpacking function, constructs a deeper active call chain to achieve generic unpacking of second-generation function extraction packers, and uses JNI function and instruction monitoring to handle third-generation virtual obfuscation packer. On this basis, we counteract a diverse array of anti-analysis techniques. We conduct extensive experiments on 5K packed Android malware samples, comparing <inline-formula> <tex-math>$\\\\textsf {Gupacker}$ </tex-math></inline-formula> with 2 commercial and 4 state-of-the-art academic unpacking tools. The results demonstrate that <inline-formula> <tex-math>$\\\\textsf {Gupacker}$ </tex-math></inline-formula> significantly improves the efficiency of Android malware unpacking with acceptable system overhead. We analyze real packed applications based on <inline-formula> <tex-math>$\\\\textsf {Gupacker}$ </tex-math></inline-formula> and found several are second-packed by attackers, including WPS for Android, with tens of millions of users. We receive and responsibly report 13 0day vulnerabilities and also assist in the remediation of all vulnerabilities.\",\"PeriodicalId\":13492,\"journal\":{\"name\":\"IEEE Transactions on Information Forensics and Security\",\"volume\":\"20 \",\"pages\":\"4338-4352\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2025-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Information Forensics and Security\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10955277/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Information Forensics and Security","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10955277/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
Gupacker: Generalized Unpacking Framework for Android Malware
Android malware authors often use packers to evade analysis. Although many unpacking tools have been proposed, they face two significant challenges: 1) They are easily impeded by anti-analysis techniques employed by packers, preventing efficient collection of hidden Dex data. 2) They are typically designed to unpack a specific packer and cannot handle malware packed with mixed packers. Consequently, many packed malware samples evade detection. To bridge this gap, we propose $\textsf {Gupacker}$ , a novel generalized unpacking framework. $\textsf {Gupacker}$ offers a generic solution for first-generation holistic packer by customizing the Android system source code. It identifies the type of packer and selects an appropriate unpacking function, constructs a deeper active call chain to achieve generic unpacking of second-generation function extraction packers, and uses JNI function and instruction monitoring to handle third-generation virtual obfuscation packer. On this basis, we counteract a diverse array of anti-analysis techniques. We conduct extensive experiments on 5K packed Android malware samples, comparing $\textsf {Gupacker}$ with 2 commercial and 4 state-of-the-art academic unpacking tools. The results demonstrate that $\textsf {Gupacker}$ significantly improves the efficiency of Android malware unpacking with acceptable system overhead. We analyze real packed applications based on $\textsf {Gupacker}$ and found several are second-packed by attackers, including WPS for Android, with tens of millions of users. We receive and responsibly report 13 0day vulnerabilities and also assist in the remediation of all vulnerabilities.
期刊介绍:
The IEEE Transactions on Information Forensics and Security covers the sciences, technologies, and applications relating to information forensics, information security, biometrics, surveillance and systems applications that incorporate these features