一种新的跨用户内核空间检测不可信执行流的动态分析基础结构

J. Hong, Xuhua Ding
{"title":"一种新的跨用户内核空间检测不可信执行流的动态分析基础结构","authors":"J. Hong, Xuhua Ding","doi":"10.1109/SP40001.2021.00024","DOIUrl":null,"url":null,"abstract":"Code instrumentation and hardware based event trapping are two primary approaches used in dynamic malware analysis systems. In this paper, we propose a new approach called Execution Flow Instrumentation (EFI) where the analyzer execution flow is interleaved with the target flow in user- and kernel-mode, at junctures flexibly chosen by the analyzer at runtime. We also propose OASIS as the system infrastructure to realize EFI with virtues of the current two approaches, however without their drawbacks. Despite being securely and transparently isolated from the target, the analyzer introspects and controls it in the same native way as instrumentation code. We have implemented a prototype of OASIS and rigorously evaluated it with various experiments including performance and anti-analysis benchmark tests. We have also conducted two EFI case studies. The first is a cross-space control flow tracer and the second includes two EFI tools working in tandem with Google Syzkaller. One tool makes a dynamic postmortem analysis according to a kernel crash report; and the other explores the behavior of a malicious kernel space device driver which evades Syzkaller logging. The studies show that EFI analyzers are well-suited for fine-grained on-demand dynamic analysis upon a malicious thread in user or kernel mode. It is easy to develop agile EFI tools as they are user-space programs.","PeriodicalId":6786,"journal":{"name":"2021 IEEE Symposium on Security and Privacy (SP)","volume":"5 1","pages":"1902-1918"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A Novel Dynamic Analysis Infrastructure to Instrument Untrusted Execution Flow Across User-Kernel Spaces\",\"authors\":\"J. Hong, Xuhua Ding\",\"doi\":\"10.1109/SP40001.2021.00024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Code instrumentation and hardware based event trapping are two primary approaches used in dynamic malware analysis systems. In this paper, we propose a new approach called Execution Flow Instrumentation (EFI) where the analyzer execution flow is interleaved with the target flow in user- and kernel-mode, at junctures flexibly chosen by the analyzer at runtime. We also propose OASIS as the system infrastructure to realize EFI with virtues of the current two approaches, however without their drawbacks. Despite being securely and transparently isolated from the target, the analyzer introspects and controls it in the same native way as instrumentation code. We have implemented a prototype of OASIS and rigorously evaluated it with various experiments including performance and anti-analysis benchmark tests. We have also conducted two EFI case studies. The first is a cross-space control flow tracer and the second includes two EFI tools working in tandem with Google Syzkaller. One tool makes a dynamic postmortem analysis according to a kernel crash report; and the other explores the behavior of a malicious kernel space device driver which evades Syzkaller logging. The studies show that EFI analyzers are well-suited for fine-grained on-demand dynamic analysis upon a malicious thread in user or kernel mode. It is easy to develop agile EFI tools as they are user-space programs.\",\"PeriodicalId\":6786,\"journal\":{\"name\":\"2021 IEEE Symposium on Security and Privacy (SP)\",\"volume\":\"5 1\",\"pages\":\"1902-1918\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE Symposium on Security and Privacy (SP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SP40001.2021.00024\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Symposium on Security and Privacy (SP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SP40001.2021.00024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

代码插装和基于硬件的事件捕获是动态恶意软件分析系统中使用的两种主要方法。在本文中,我们提出了一种新的方法,称为执行流仪表(EFI),其中分析器的执行流在用户模式和内核模式下与目标流交错,在运行时分析器灵活选择的节点上。我们还提出OASIS作为系统基础设施来实现EFI,它具有当前两种方法的优点,但没有它们的缺点。尽管安全且透明地与目标隔离,分析器还是以与检测代码相同的本机方式对其进行自省和控制。我们已经实现了OASIS的原型,并通过包括性能和反分析基准测试在内的各种实验对其进行了严格的评估。我们还进行了两个EFI案例研究。第一个是跨空间控制流跟踪器,第二个包括两个EFI工具与Google Syzkaller协同工作。一个工具根据内核崩溃报告进行动态事后分析;另一个则探讨了恶意内核空间设备驱动程序的行为,该驱动程序可以逃避Syzkaller日志记录。研究表明,EFI分析器非常适合在用户模式或内核模式下对恶意线程进行细粒度的按需动态分析。开发敏捷EFI工具很容易,因为它们是用户空间程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A Novel Dynamic Analysis Infrastructure to Instrument Untrusted Execution Flow Across User-Kernel Spaces
Code instrumentation and hardware based event trapping are two primary approaches used in dynamic malware analysis systems. In this paper, we propose a new approach called Execution Flow Instrumentation (EFI) where the analyzer execution flow is interleaved with the target flow in user- and kernel-mode, at junctures flexibly chosen by the analyzer at runtime. We also propose OASIS as the system infrastructure to realize EFI with virtues of the current two approaches, however without their drawbacks. Despite being securely and transparently isolated from the target, the analyzer introspects and controls it in the same native way as instrumentation code. We have implemented a prototype of OASIS and rigorously evaluated it with various experiments including performance and anti-analysis benchmark tests. We have also conducted two EFI case studies. The first is a cross-space control flow tracer and the second includes two EFI tools working in tandem with Google Syzkaller. One tool makes a dynamic postmortem analysis according to a kernel crash report; and the other explores the behavior of a malicious kernel space device driver which evades Syzkaller logging. The studies show that EFI analyzers are well-suited for fine-grained on-demand dynamic analysis upon a malicious thread in user or kernel mode. It is easy to develop agile EFI tools as they are user-space programs.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A2L: Anonymous Atomic Locks for Scalability in Payment Channel Hubs High-Assurance Cryptography in the Spectre Era An I/O Separation Model for Formal Verification of Kernel Implementations Trust, But Verify: A Longitudinal Analysis Of Android OEM Compliance and Customization HackEd: A Pedagogical Analysis of Online Vulnerability Discovery Exercises
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1