Walls Have Ears: Demystifying Notification Listener Usage in Android Apps

The Notification Listener Service (NLS) in Android allows third-party apps to monitor and process device notifications, enabling powerful features but also introducing security and privacy risks. Despite the special permission required to access NLS, it has been recurrently exploited by malicious actors. However, there is a lack of systematic investigation into NLS usage patterns and their security implications. In this paper, we propose NLRadar, a hybrid approach combining static analysis and LLM to examine NLS usage in Android apps. We apply NLRadar to a large scale of apps, including both malware and regular apps, to demystify NLS usage and to uncover abuses. Our analysis reveals that NLS is heavily abused, with interesting discoveries such as apps insecurely storing social media messages, exploiting NLS for destructive competition or SMS credential stealing, and leveraging NLS to spread promotional messages or even malicious links. We also find undisclosed changes in NLS usage through app updates and inadequate disclosure in privacy policies. Our findings emphasize the need for more rigorous vetting of NLS usage and better developer education on responsible NLS practices.

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Publication Details

Journal
Proceedings of the ACM on software engineering.
Published
2025-06-22
DOI
https://doi.org/10.1145/3728898
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Walls Have Ears: Demystifying Notification Listener Usage in Android Apps

Yanjie Zhao, Tianming Liu, Lin Zhang, Chao Wang et al.
Proceedings of the ACM on software engineering.
Advanced Malware Detection Techniques
article

Walls Have Ears: Demystifying Notification Listener Usage in Android Apps

Yanjie Zhao, Tianming Liu, Lin Zhang, Chao Wang, Jiapeng Deng, Haoyu Wang
article en

Abstract

The Notification Listener Service (NLS) in Android allows third-party apps to monitor and process device notifications, enabling powerful features but also introducing security and privacy risks. Despite the special permission required to access NLS, it has been recurrently exploited by malicious actors. However, there is a lack of systematic investigation into NLS usage patterns and their security implications. In this paper, we propose NLRadar, a hybrid approach combining static analysis and LLM to examine NLS usage in Android apps. We apply NLRadar to a large scale of apps, including both malware and regular apps, to demystify NLS usage and to uncover abuses. Our analysis reveals that NLS is heavily abused, with interesting discoveries such as apps insecurely storing social media messages, exploiting NLS for destructive competition or SMS credential stealing, and leveraging NLS to spread promotional messages or even malicious links. We also find undisclosed changes in NLS usage through app updates and inadequate disclosure in privacy policies. Our findings emphasize the need for more rigorous vetting of NLS usage and better developer education on responsible NLS practices.

Proceedings of the ACM on software engineering.Vol. 2(ISSTA)
National Computer Network Emergency Response Technical Team/Coordination Center of Chinar (CN), Huazhong University of Science and Technology (CN), Monash University (AU)
Peace, Justice and strong institutions
Openalex Percentile: Top 83%
Advanced Malware Detection Techniques
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Walls Have Ears: Demystifying Notification Listener Usage in Android Apps — Yanjie Zhao, Tianming Liu, et al. · Proceedings of the ACM on software engineering. (2025) | TGRS Research Map | TGRS