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-m...

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Main Authors: HONG, Jiaqi, DING, Xuhua
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Language:English
Published: Institutional Knowledge at Singapore Management University 2021
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Online Access:https://ink.library.smu.edu.sg/sis_research/5610
https://ink.library.smu.edu.sg/context/sis_research/article/6613/viewcontent/PID6498953.pdf
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spelling sg-smu-ink.sis_research-66132021-01-07T13:50:31Z A novel dynamic analysis infrastructure to instrument untrusted execution flow across user-kernel spaces HONG, Jiaqi DING, Xuhua 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. 2021-05-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5610 info:doi/10.1109/SP40001.2021.00024 https://ink.library.smu.edu.sg/context/sis_research/article/6613/viewcontent/PID6498953.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Information Security
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Information Security
spellingShingle Information Security
HONG, Jiaqi
DING, Xuhua
A novel dynamic analysis infrastructure to instrument untrusted execution flow across user-kernel spaces
description 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.
format text
author HONG, Jiaqi
DING, Xuhua
author_facet HONG, Jiaqi
DING, Xuhua
author_sort HONG, Jiaqi
title A novel dynamic analysis infrastructure to instrument untrusted execution flow across user-kernel spaces
title_short A novel dynamic analysis infrastructure to instrument untrusted execution flow across user-kernel spaces
title_full A novel dynamic analysis infrastructure to instrument untrusted execution flow across user-kernel spaces
title_fullStr A novel dynamic analysis infrastructure to instrument untrusted execution flow across user-kernel spaces
title_full_unstemmed A novel dynamic analysis infrastructure to instrument untrusted execution flow across user-kernel spaces
title_sort novel dynamic analysis infrastructure to instrument untrusted execution flow across user-kernel spaces
publisher Institutional Knowledge at Singapore Management University
publishDate 2021
url https://ink.library.smu.edu.sg/sis_research/5610
https://ink.library.smu.edu.sg/context/sis_research/article/6613/viewcontent/PID6498953.pdf
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