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CLC number: TP309
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2020-12-29
Cited: 0
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Citations: Bibtex RefMan EndNote GB/T7714
Generic, efficient, and effective deobfuscation and semantic-aware attack detection for PowerShell scripts
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Chunlin XIONG, Zhenyuan LI, Yan CHEN, Tiantian ZHU, Jian WANG, Hai YANG, Wei RUAN. Generic, efficient, and effective deobfuscation and semantic-aware attack detection for PowerShell scripts[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(3): 361-381.
@article{title="Generic, efficient, and effective deobfuscation and semantic-aware attack detection for PowerShell scripts",
author="Chunlin XIONG, Zhenyuan LI, Yan CHEN, Tiantian ZHU, Jian WANG, Hai YANG, Wei RUAN",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="23",
number="3",
pages="361-381",
year="2022",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2000436"
}
%0 Journal Article
%T Generic, efficient, and effective deobfuscation and semantic-aware attack detection for PowerShell scripts
%A Chunlin XIONG
%A Zhenyuan LI
%A Yan CHEN
%A Tiantian ZHU
%A Jian WANG
%A Hai YANG
%A Wei RUAN
%J Frontiers of Information Technology & Electronic Engineering
%V 23
%N 3
%P 361-381
%@ 2095-9184
%D 2022
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2000436
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T1 - Generic, efficient, and effective deobfuscation and semantic-aware attack detection for PowerShell scripts
A1 - Chunlin XIONG
A1 - Zhenyuan LI
A1 - Yan CHEN
A1 - Tiantian ZHU
A1 - Jian WANG
A1 - Hai YANG
A1 - Wei RUAN
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 23
IS - 3
SP - 361
EP - 381
%@ 2095-9184
Y1 - 2022
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2000436
Abstract: In recent years, powerShell has increasingly been reported as appearing in a variety of cyber attacks. However, because the powerShell language is dynamic by design and can construct script fragments at different levels, state-of-the-art static analysis based powerShell attack detection approaches are inherently vulnerable to obfuscations. In this paper, we design the first generic, effective, and lightweight deobfuscation approach for powerShell scripts. To precisely identify the obfuscated script fragments, we define obfuscation based on the differences in the impacts on the abstract syntax trees of powerShell scripts and propose a novel emulation-based recovery technology. Furthermore, we design the first semantic-aware powerShell attack detection system that leverages the classic objective-oriented association mining algorithm and newly identifies 31 semantic signatures. The experimental results on 2342 benign samples and 4141 malicious samples show that our deobfuscation method takes less than 0.5 s on average and increases the similarity between the obfuscated and original scripts from 0.5% to 93.2%. By deploying our deobfuscation method, the attack detection rates for Windows Defender and VirusTotal increase substantially from 0.33% and 2.65% to 78.9% and 94.0%, respectively. Moreover, our detection system outperforms both existing tools with a 96.7% true positive rate and a 0% false positive rate on average.
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