PriviSense: A Frida-Based Framework for Multi-Sensor Spoofing on Android

Fuente: arXiv
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Main Authors: Khalilov, Ibrahim, Chen, Chaoran, Xiao, Ziang, Li, Tianshi, Li, Toby Jia-Jun, Yao, Yaxing
Format: Preprint
Published: 2026
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author Khalilov, Ibrahim
Chen, Chaoran
Xiao, Ziang
Li, Tianshi
Li, Toby Jia-Jun
Yao, Yaxing
author_facet Khalilov, Ibrahim
Chen, Chaoran
Xiao, Ziang
Li, Tianshi
Li, Toby Jia-Jun
Yao, Yaxing
contents Mobile apps increasingly rely on real-time sensor and system data to adapt their behavior to user context. While emulators and instrumented builds offer partial solutions, they often fail to support reproducible testing of context-sensitive app behavior on physical devices. We present PriviSense, a Frida-based, on-device toolkit for runtime spoofing of sensor and system signals on rooted Android devices. PriviSense can script and inject time-varying sensor streams (accelerometer, gyroscope, step counter) and system values (battery level, system time, device metadata) into unmodified apps, enabling reproducible on-device experiments without emulators or app rewrites. Our demo validates real-time spoofing on a rooted Android device across five representative sensor-visualization apps. By supporting scriptable and reversible manipulation of these values, PriviSense facilitates testing of app logic, uncovering of context-based behaviors, and privacy-focused analysis. To ensure ethical use, the code is shared upon request with verified researchers. Tool Guide: How to Run PriviSense on Rooted Android https://bit.ly/privisense-guide Demonstration video: https://www.youtube.com/watch?v=4Qwnogcc3pw
format Preprint
id arxiv_https___arxiv_org_abs_2601_22414
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle PriviSense: A Frida-Based Framework for Multi-Sensor Spoofing on Android
Khalilov, Ibrahim
Chen, Chaoran
Xiao, Ziang
Li, Tianshi
Li, Toby Jia-Jun
Yao, Yaxing
Software Engineering
Cryptography and Security
Human-Computer Interaction
Mobile apps increasingly rely on real-time sensor and system data to adapt their behavior to user context. While emulators and instrumented builds offer partial solutions, they often fail to support reproducible testing of context-sensitive app behavior on physical devices. We present PriviSense, a Frida-based, on-device toolkit for runtime spoofing of sensor and system signals on rooted Android devices. PriviSense can script and inject time-varying sensor streams (accelerometer, gyroscope, step counter) and system values (battery level, system time, device metadata) into unmodified apps, enabling reproducible on-device experiments without emulators or app rewrites. Our demo validates real-time spoofing on a rooted Android device across five representative sensor-visualization apps. By supporting scriptable and reversible manipulation of these values, PriviSense facilitates testing of app logic, uncovering of context-based behaviors, and privacy-focused analysis. To ensure ethical use, the code is shared upon request with verified researchers. Tool Guide: How to Run PriviSense on Rooted Android https://bit.ly/privisense-guide Demonstration video: https://www.youtube.com/watch?v=4Qwnogcc3pw
title PriviSense: A Frida-Based Framework for Multi-Sensor Spoofing on Android
topic Software Engineering
Cryptography and Security
Human-Computer Interaction
url https://arxiv.org/abs/2601.22414