USENIX Security2017Top-tier venue
Ninja: Towards Transparent Tracing and Debugging on ARM
Zhenyu Ning, Fengwei Zhang
Abstract
Existing malware analysis platforms leave detectable fingerprints like uncommon string properties in QEMU, signatures in Android Java virtual machine, and artifacts in Linux kernel profiles. Since these fingerprints provide the malware a chance to split its behavior depending on whether the analysis system is present or not, existing analysis systems are not sufficient to analyze the sophisticated malware. In this paper, we propose NINJA, a transparent malware analysis framework on ARM platform with low artifacts. NINJA leverages a hardware-assisted isolated execution environment Trust-Zone to transparently trace and debug a target application with the help of Performance Monitor Unit and Embedded Trace Macrocell. NINJA does not modify system software and is OS-agnostic on ARM platform. We implement a prototype of NINJA (i.e., tracing and debugging subsystems), and the experiment results show that NINJA is efficient and transparent for malware analysis.
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Install the CLIlune papers fulltext f141a26a-25d6-40cc-bb66-874507b4ff64Cited by top-tier papers14
- Understanding the Security of ARM Debugging FeaturesZhenyu Ning, Fengwei ZhangS&P 2019 · 41 citations
- Happer: Unpacking Android Apps via a Hardware-Assisted ApproachLei Xue, Hao Zhou, Xiapu Luo, Yajin Zhou et al.S&P 2021 · 29 citations
- : Non-intrusive Feedback-driven Fuzzing for Microcontroller FirmwareWenqiang Li, Jiameng Shi, Fengjun Li, Jingqiang Lin et al.ICSE 2022 · 27 citations
- NCScope: hardware-assisted analyzer for native code in Android appsHao Zhou, Shuohan Wu, Xiapu Luo, Ting Wang et al.ISSTA 2022 · 16 citations
- HyperDbg: Reinventing Hardware-Assisted DebuggingMohammad Sina Karvandi, MohammadHosein Gholamrezaei, Saleh Khalaj Monfared, Soroush Meghdadi Zanjani et al.CCS 2022 · 10 citations
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