A Risk Estimation Study of Native Code Vulnerabilities in Android Applications
Silvia Lucia Sanna, Diego Soi, Davide Maiorca, Giorgio Fumera, Giorgio, Giacinto

TL;DR
This paper introduces a rapid risk assessment method for detecting vulnerabilities in native C/C++ code within Android applications, enabling developers to identify and patch security issues before release.
Contribution
It presents a novel fast, risk-based approach combining regex detection and vulnerability scoring to evaluate native code risks in large-scale Android app analysis.
Findings
Over 60% of analyzed apps contain native code.
Many apps have known vulnerabilities in popular libraries.
The approach effectively identifies high-risk native code in large datasets.
Abstract
Android is the most used Operating System worldwide for mobile devices, with hundreds of thousands of apps downloaded daily. Although these apps are primarily written in Java and Kotlin, advanced functionalities such as graphics or cryptography are provided through native C/C++ libraries. These libraries can be affected by common vulnerabilities in C/C++ code (e.g., memory errors such as buffer overflow), through which attackers can read/modify data or execute arbitrary code. The detection and assessment of vulnerabilities in Android native code have only been recently explored by previous research work. In this paper, we propose a fast risk-based approach that provides a risk score related to the native part of an Android application. In this way, before an app is released, the developer can check if the app may contain vulnerabilities in the Native Code and, if present, patch them to…
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Taxonomy
TopicsAdvanced Malware Detection Techniques · Mobile and Web Applications · Web Application Security Vulnerabilities
