Authors:
Lei Zhang, Zhemin Yang, Yuyu He, Zhenyu Zhang, Zhiyun Qian, Geng Hong, Yuan Zhang, Min Yang
Publication:
In Proceedings of the 25th ACM Conference on Computer and Communications Security (CCS 2018).
Abstract:
As we show in the paper, there are in fact more input validations acting as security checks than permission checks, rendering them a critical foundation for Android framework. Unfortunately, these validations are unstructured, ill-defined, and fragmented, making it challenging to analyze. To this end, we design and implement a tool, called Invetter, that combines machine learning and static analysis to locate sensitive input validations that are problematic in system services. By applying Invetter to 4 different AOSP code-bases and 4 vendor-customized images, we locate 103 candidate insecure validations. Among the true positives, we are able to confirm that at least 20 of them are truly exploitable vulnerabilities by constructing various attacks such as privilege escalation and private information leakage.
LW021 Invetter Locating Insecure Input Validations in Android Services.pdf