FirmwareDroid: Towards Automated Static Analysis of Pre-Installed Android Apps

被引:1
|
作者
Sutter, Thomas [1 ]
Tellenbach, Bernhard [2 ]
机构
[1] Zurich Univ Appl Sci, Inst Appl Informat Technol, Winterthur, Switzerland
[2] Armasuisse, Cyber Def Campus, Zurich, Switzerland
来源
2023 IEEE/ACM 10TH INTERNATIONAL CONFERENCE ON MOBILE SOFTWARE ENGINEERING AND SYSTEMS, MOBILESOFT | 2023年
关键词
Android Firmware; Pre-Installed Apps; Static Analysis; Security; Vulnerability;
D O I
10.1109/MOBILSoft59058.2023.00009
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Supply chain attacks are an evolving threat to the IoT and mobile landscape. Recent malware findings have shown that even sizeable mobile phone vendors cannot defend their operating systems fully against pre-installed malware. Detecting and mitigating malware and software vulnerabilities on Android firmware is a challenging task requiring expertise in Android internals, such as customised firmware formats. Moreover, as users cannot choose what software is pre-installed on their devices, there is a fundamental lack of transparency and control. To make Android firmware analysis more accessible and regain some transparency, we present FirmwareDroid, a novel opensource security framework for Android firmware analysis that automates the extraction and analysis of pre-installed software. FirmwareDroid streamlines the process of software extraction from Android firmware for static security and privacy assessments. With FirmwareDroid, we lay the groundwork for researchers to automate the security assessment of Android firmware at scale, and we demonstrated the capabilities of FirmwareDroid by analysing 5,728 Android firmware samples from various vendors. We analysed 75,141 unique pre-installed Android applications to study how common advertising tracker libraries (a piece of software that collects user usage data) are used and which permissions pre-installed Android apps inherit. We conclude that 20.53% of all apps in our dataset include advertising trackers and that 88.14% of all used permissions are signature-based.
引用
收藏
页码:12 / 22
页数:11
相关论文
共 41 条
  • [31] AndroShield: Automated Android Applications Vulnerability Detection, a Hybrid Static and Dynamic Analysis Approach
    Amin, Amr
    Eldessouki, Amgad
    Magdy, Menna Tullah
    Abdeen, Nouran
    Hindy, Hanan
    Hegazy, Islam
    INFORMATION, 2019, 10 (10)
  • [32] Automated static analysis and classification of Android malware using permission and API calls models
    Skovoroda, Anastasia
    Gamayunov, Dennis
    2017 15TH ANNUAL CONFERENCE ON PRIVACY, SECURITY AND TRUST (PST), 2017, : 243 - 252
  • [33] Fixing Resource Leaks in Android Apps with Light-weight Static Analysis and Low-overhead Instrumentation
    Liu, Jierui
    Wu, Tianyong
    Yan, Jun
    Zhang, Jian
    2016 IEEE 27TH INTERNATIONAL SYMPOSIUM ON SOFTWARE RELIABILITY ENGINEERING (ISSRE), 2016, : 342 - 352
  • [34] Evaluating State-of-the-Art Free and Open Source Static Analysis Tools against Buffer Errors in Android Apps
    Aloraini, Bushra
    Nagappan, Meiyappan
    2017 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE AND EVOLUTION (ICSME), 2017, : 295 - 306
  • [35] Detecting the Inconsistency between Android Apps' Data Collection and Google Play's Data Safety Using Static Analysis
    Baalous, Rawan
    Althobaiti, Alanoud
    Alyoubi, Dareen
    Alzahrani, Rama
    Aljohani, Mona
    CYBERNETICS AND INFORMATION TECHNOLOGIES, 2025, 25 (01) : 110 - 125
  • [36] Right to Know, Right to Refuse: Towards UI Perception-Based Automated Fine-Grained Permission Controls for Android Apps
    Malviya, Vikas K.
    Leow, Chee Wei
    Kasthuri, Ashok
    Tun, Yan Naing
    Shar, Lwin Khin
    Jiang, Lingxiao
    PROCEEDINGS OF THE 37TH IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING, ASE 2022, 2022,
  • [37] Towards More Reliable Automated Program Repair by Integrating Static Analysis Techniques
    Al-Bataineh, Omar, I
    Grishina, Anastasiia
    Moonen, Leon
    2021 IEEE 21ST INTERNATIONAL CONFERENCE ON SOFTWARE QUALITY, RELIABILITY AND SECURITY (QRS 2021), 2021, : 654 - 663
  • [38] Towards Bridging the Gap Between Dalvik Bytecode and Native Code During Static Analysis of Android Applications
    Lantz, Patrik
    Johansson, Bjorn
    2015 INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE (IWCMC), 2015, : 587 - 593
  • [39] Towards a fair comparison and realistic evaluation framework of android malware detectors based on static analysis and machine learning
    Molina-Coronado, Borja
    Mori, Usue
    Mendiburu, Alexander
    Miguel-Alonso, Jose
    COMPUTERS & SECURITY, 2023, 124
  • [40] SAMLDroid: A Static Taint Analysis and Machine Learning Combined High-Accuracy Method for Identifying Android Apps with Location Privacy Leakage Risks
    Hu, Guangwu
    Zhang, Bin
    Xiao, Xi
    Zhang, Weizhe
    Liao, Long
    Zhou, Ying
    Yan, Xia
    ENTROPY, 2021, 23 (11)