| Autor: |
Yeongung Park, Seokwoo Choi, Un Yeong Choi, Haimin Jin, Nurul Harzira Mohamad Nor, Yongsu Park |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2045-2322 |
| DOI: |
10.1038/s41598-024-65374-w |
| Popis: |
Abstract As IoT devices are being widely used, malicious code is increasingly appearing in Linux environments. Sophisticated Linux malware employs various evasive techniques to deter analysis. The embedded trace microcell (ETM) supported by modern Arm CPUs is a suitable hardware tracer for analyzing evasive malware because it is almost artifact-free and has negligible overhead. In this paper, we present an efficient method to automatically find debugger-detection routines using the ETM hardware tracer. The proposed scheme reconstructs the execution flow of the compiled binary code from ETM trace data. In addition, it automatically identifies and patches the debugger-detection routine by comparing two traces (with and without the debugger). The proposed method was implemented using the Ghidra plug-in program, which is one of the most widely used disassemblers. To verify its effectiveness, 15 debugger-detection techniques were investigated in the Arm-Linux environment to determine whether they could be detected. We also confirmed that our implementation works successfully for the popular malicious Mirai malware in Linux. Experiments were further conducted on 423 malware samples collected from the Internet, demonstrating that our implementation works well for real malware samples. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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