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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.
[1]AbdelKhalek M, Shosha A, 2017. JSDES: an automated de-obfuscation system for malicious JavaScript. Proc 12th Int Conf on Availability, Reliability and Security, p.1-13.
[2]Ackerman G, Cole R, Thompson A, et al., 2018. OVERRULED: Containing a Potentially Destructive Adversary. https://bit.ly/2tSUacy [Accessed on Aug. 8, 2020].
[3]Acornjs, 2013. Acorn. https://bit.ly/2BPzkyw [Accessed on Aug. 8, 2020].
[4]Aebersold S, Kryszczuk K, Paganoni S, et al., 2016. Detecting obfuscated JavaScript using machine learning. 11th Int Conf on Internet Monitoring and Protection, p.11-17.
[5]Ahl I, 2017. Threat Research: Privileges and Credentials: Phished at the Request of Counsel. https://bit.ly/2RaIk5o [Accessed on Aug. 8, 2020].
[6]AST Explorer, 2015. AST Explorer. https://astexplorer.net/ [Accessed on Aug. 8, 2020].
[7]Barak B, Goldreich O, Impagliazzo R, et al., 2012. On the (im)possibility of obfuscating programs. J ACM, 59(2):6.
[8]Bohannon D, 2016. Invoke-Obfuscation. https://bit.ly/2TIEwLN [Accessed on Aug. 8, 2020].
[9]Bohannon D, 2017a. ObfuscatedEmpire–Use an Obfuscated, In-memory PowerShell C2 Channel to Evade AV Signatures. https://bit.ly/36UVYjC [Accessed on Aug. 8, 2020].
[10]Bohannon D, 2017b. PowerShellObfuscation Detection Framework. https://bit.ly/2RhakUP [Accessed on Aug. 8, 2020].
[11]Borgelt C, 2005. An implementation of the FP-growth algorithm. Proc 1st Int Workshop on Open Source Data Mining: Frequent Pattern Mining Implementations, p.1-5.
[12]Canali D, Cova M, Vigna G, et al., 2011. Prophiler: a fast filter for the large-scale detection of malicious web pages. Proc 20th Int Conf on World Wide Web, p.197-206.
[13]Candid W, 2016. The Increased Use of PowerShell in Attacks. https://symc.ly/2NmazwO [Accessed on Aug. 8, 2020].
[14]Christodorescu M, Jha S, Seshia SA, et al., 2005. Semantics-aware malware detection. Proc IEEE Symp on Security and Privacy, p.32-46.
[15]Cova M, Kruegel C, Vigna G, 2010. Detection and analysis of drive-by-download attacks and malicious JavaScript code. Proc 19th Int Conf on World Wide Web, p.281-290.
[16]CrowdStrike, 2014. Free Automated Malware Analysis Service. https://bit.ly/36SUUgd [Accessed on Aug. 8, 2020].
[17]CrowdStrike, 2018. Who Needs Malware? How Adversaries Use Fileless Attacks to Evade Your Security. https://bit.ly/2HZB23i [Accessed on Aug. 8, 2020].
[18]Curtsinger C, Livshits B, Zorn B, et al., 2011. ZOZZLE: fast and precise in-browser JavaScript malware detection. Proc 20th USENIX Conf on Security, p.33-48.
[19]Diggs R, 2017. Pulling Back the Curtains on EncodedCommand PowerShell Attacks. https://bit.ly/30jVNMr [Accessed on Aug. 8, 2020].
[20]EmpireProject, 2015. Empire Is a PowerShell and Python Post-Exploitation Agent. https://bit.ly/36P13du [Accessed on Aug. 8, 2020].
[21]FOLDOC, 1994. Free On-line Dictionary of Computing: Abstract Syntax Tree. https://foldoc.org/abstract+syntax+tree [Accessed on Aug. 8, 2020].
[22]Fredrikson M, Jha S, Christodorescu M, et al., 2010. Synthesizing near-optimal malware specifications from suspicious behaviors. Proc IEEE Symp on Security and Privacy, p.45-60.
[23]Google, 2004. VirusTotal. https://bit.ly/3a3Pfpz [Accessed on Aug. 8, 2020].
[24]Google, 2011. Traceur-Compiler. https://bit.ly/2BW2hZP [Accessed on Aug. 8, 2020].
[25]Hendler D, Kels S, Rubin A, 2018. Detecting malicious PowerShell commands using deep neural networks. Proc Asia Conf on Computer and Communications Security, p.187-197.
[26]Hidayat A, 2012. ECMAScript Parsing Infrastructure for Multipurpose Analysis. https://esprima.org/ [Accessed on Aug. 8, 2020].
[27]Jodavi M, Abadi M, Parhizkar E, 2015. JSObfusDetector: a binary PSO-based one-class classifier ensemble to detect obfuscated JavaScript code. Proc Int Symp on Artificial Intelligence and Signal Processing, p.322-327.
[28]Kachalov T, 2016. JavaScript-Obfuscator. https://bit.ly/3cSvP7a [Accessed on Aug. 8, 2020].
[29]Kannumittal, 2018. Difference b/w a Programming & Scripting Language. https://www.codingninjas.com/blog/2018/12/08/difference-between-a-programming-language-and-a-scripting-language/
[30]Kaplan S, Livshits B, Zorn B, et al., 2011. “NOFUS: Automatically Detecting” String.fromCharCode(32) “ObFuSCateD” to LowerCase() “JavaScript Code”. Technical Report MSR-TR 2011-57. Microsoft Research.
[31]Koschke R, Falke R, Frenzel P, 2006. Clone detection using abstract syntax suffix trees. Proc 13th Working Conf on Reverse Engineering, p.253-262.
[32]Li ZY, Chen QA, Xiong CL, et al., 2019. Effective and light-weight deobfuscation and semantic-aware attack detection for PowerShell scripts. Proc ACM SIGSAC Conf on Computer and Communications Security, p.1831-1847.
[33]Liu C, Xia B, Yu M, et al., 2018. PSDEM: a feasible de-obfuscation method for malicious PowerShell detection. Proc IEEE Symp on Computers and Communications, p.825-831.
[34]Lu G, Debray S, 2012. Automatic simplification of obfuscated JavaScript code: a semantics-based approach. Proc IEEE 6th Int Conf on Software Security and Reliability, p.31-40.
[35]Maniar V, 2018. PowerShell-RAT. https://bit.ly/2uOD7ZH [Accessed on Aug. 8, 2020].
[36]Mateas M, Montfort N, 2005. A box, darkly: obfuscation, weird languages, and code aesthetics. Proc 6th Digital Arts and Culture Conf, p.144-153.
[37]Microsoft, 2014. Submit a File for Malware Analysis—Microsoft Security Intelligence. https://bit.ly/2TgVYXo [Accessed on Aug. 8, 2020].
[38]Microsoft, 2019. Antimalware Scan Interface (AMSI). https://bit.ly/3hHhXBJ [Accessed on Aug. 8, 2020].
[39]Mishoo, 2015. UglifyJS. https://bit.ly/30wOWkM [Accessed on Aug. 8, 2020].
[40]MITRE, 2015. MITRE ATT & CK. https://attack.mitre.org/ [Accessed on Aug. 8, 2020].
[41]MITRE, 2020. Technique: PowerShell-MITRE ATT&CKTM. https://bit.ly/36SVSsR [Accessed on Aug. 8, 2020].
[42]PowerShellMafia, 2012. PowerSploit: a PowerShell Post-Exploitation Framework—PowerShellMafia/ PowerSploit. https://bit.ly/36STQJ9 [Accessed on Aug. 8, 2020].
[43]R3MRUM, 2018. PowerShell Script for Deobfuscating Encoded PowerShell Scripts: R3mrum/PSDecode https://github.com/R3MRUM/PSDecode [Accessed on Aug. 8, 2020].
[44]Reactor NET, 2003. Code Virtualization. https://www.eziriz.com [Accessed on Aug. 8, 2020].
[45]Rieck K, Krueger T, Dewald A, 2010. Cujo: efficient detection and prevention of drive-by-download attacks. Proc 26th Annual Computer Security Applications Conf, p.31-39.
[46]Rubin A, Kels S, Hendler D, 2019. AMSI-based detection of malicious PowerShell code using contextual embeddings. https://arxiv.org/abs/1905.09538
[47]Rusak G, Al-Dujaili A, O’Reilly UM, 2018. AST-based deep learning for detecting malicious PowerShell. Proc ACM SIGSAC Conf on Computer and Communications Security, p.2276-2278.
[48]Samratashok, 2020. What Is PowerShell? https://bit.ly/3f8U5DS [Accessed on Aug. 8, 2020].
[49]Scraper W, 2019. Web Scraper. https://www.webscraper.io/ [Accessed on Aug. 8, 2020].
[50]ShapeSecurity, 2015. Shift-parser-js. https://bit.ly/3fe0HRj [Accessed on Aug. 8, 2020].
[51]Shen YD, Zhang Z, Yang Q, 2002. Objective-oriented utility-based association mining. Proc IEEE Int Conf on Data Mining, p.426-433.
[52]Symantec, 2018. Security Center White Papers | Symantec. https://symc.ly/2TlKphr [Accessed on Aug. 8, 2020].
[53]Tobias W, 2018. New Obfuscation Modes. https://bit.ly/2FJhJae [Accessed on Aug. 8, 2020].
[54]Ugarte D, Maiorca D, Cara F, et al., 2019. PowerDrive: accurate de-obfuscation and analysis of PowerShell malware. Proc 16th Int Conf on Detection of Intrusions and Malware, and Vulnerability Assessment, p.240-259.
[55]Wueest C, Anand H, 2017. ISTR Living off the Land and Fileless Attack Techniques. https://symc.ly/2FP6v3X [Accessed on Aug. 8, 2020].
[56]Wueest C, Stephen D, 2016. The Increased Use of PowerShell in Attacks. https://symc.ly/35Qj1ef [Accessed on Aug. 8, 2020].
[57]Xiong CL, Zhu TT, Dong WH, et al., 2022. Conan: a practical real-time APT detection system with high accuracy and efficiency. IEEE Trans Depend Sec Comput, 19(1):551-565.
[58]Xu W, Zhang FF, Zhu SC, 2012. The power of obfuscation techniques in malicious JavaScript code: a measurement study. Proc 7th Int Conf on Malicious and Unwanted Software, p.9-16.
[59]Ye YF, Wang DD, Li T, et al., 2008. An intelligent PE-malware detection system based on association mining. J Comput Virol, 4(4):323-334.
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