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      Multi-path exploration guided by taint and probability against evasive malware

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          Abstract

          Static analysis is often impeded by malware obfuscation techniques, such as encryption and packing, whereas dynamic analysis tends to be more resistant to obfuscation by leveraging concrete execution information. Unfortunately, malware can employ evasive techniques to detect the analysis environment and alter its behavior accordingly. While known evasive techniques can be explicitly dismantled, the challenge lies in generically dismantling evasions without full knowledge of their conditions or implementations, such as logic bombs that rely on uncertain conditions, let alone unsupported evasive techniques, which contain evasions without corresponding dismantling strategies and those leveraging unknown implementations. In this paper, we present Antitoxin, a prototype for automatically exploring evasive malware. Antitoxin utilizes multi-path exploration guided by taint analysis and probability calculations to effectively dismantle evasive techniques. The probabilities of branch execution are derived from dynamic coverage, while taint analysis helps identify paths associated with evasive techniques that rely on uncertain conditions. Subsequently, Antitoxin prioritizes branches with lower execution probabilities and those influenced by taint analysis for multi-path exploration. This is achieved through forced execution, which forcefully sets the outcomes of branches on selected paths. Additionally, Antitoxin employs active anti-evasion countermeasures to dismantle known evasive techniques, thereby reducing exploration overhead. Furthermore, Antitoxin provides valuable insights into sensitive behaviors, facilitating deeper manual analysis. Our experiments on a set of highly evasive samples demonstrate that Antitoxin can effectively dismantle evasive techniques in a generic manner. The probability calculations guide the multi-path exploration of evasions without requiring prior knowledge of their conditions or implementations, enabling the dismantling of unsupported techniques such as C2 and significantly improving efficiency compared to linear exploration when dealing with complex control flows. Additionally, taint analysis can accurately identify branches related to logic bombs, facilitating preferential exploration.

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            A gentle introduction to genetic algorithms. Genetic algorithms revisited: mathematical foundations. Computer implementation of a genetic algorithm. Some applications of genetic algorithms. Advanced operators and techniques in genetic search. Introduction to genetics-based machine learning. Applications of genetics-based machine learning. A look back, a glance ahead. A review of combinatorics and elementary probability. Pascal with random number generation for fortran, basic, and cobol programmers. A simple genetic algorithm (SGA) in pascal. A simple classifier system(SCS) in pascal. Partition coefficient transforms for problem-coding analysis.
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              Limits of Static Analysis for Malware Detection

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                Author and article information

                Contributors
                Journal
                sands
                https://sands.edpsciences.org
                Security and Safety
                Security and Safety
                EDP Sciences and CSPM
                2826-1275
                05 September 2023
                2023
                05 September 2023
                05 September 2023
                : 2
                : ( publisher-idID: sands/2023/01 )
                : 2023023
                Affiliations
                [1 ] National Engineering Research Center for Big Data Technology and System, , Wuhan, 430074, China,
                [2 ] Services Computing Technology and System Lab, Cluster and Grid Computing Lab, , Wuhan, 430074, China,
                [3 ] Hubei Key Laboratory of Distributed System Security, Hubei Engineering Research Center on Big Data Security, , Wuhan, 430074, China,
                [4 ] School of Cyber Science and Engineering, Huazhong University of Science and Technology, , Wuhan, 430074, China,
                [5 ] School of Computer Science and Technology, Huazhong University of Science and Technology, , Wuhan, 430074, China,
                [6 ] Jinyinhu Laboratory, , Wuhan, 430040, China,
                Author notes
                [* ]Corresponding authors (email: wzqiang@ 123456hust.edu.cn )
                Article
                sands20230021
                10.1051/sands/2023023
                1d2f584b-5175-4519-9d36-f6fa1f32074b
                © The Author(s) 2023. Published by EDP Sciences and China Science Publishing & Media Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 08 May 2023
                : 20 June 2023
                : 11 August 2023
                Page count
                Figures: 8, Tables: 12, Equations: 4, References: 34, Pages: 24
                Funding
                Funded by: National Natural Science Foundation of China http://dx.doi.org/10.13039/501100001809
                Award ID: Grant No. 62272181
                Categories
                Research Article
                Other Fields
                Custom metadata
                Security and Safety, Vol. 2, 2023023 (2023)
                2023
                2023
                2023
                yes

                evasion detection,taint analysis,forced execution,dynamic binary instrumentation,Malware analysis

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