CoLaFUZE: Coverage-guided and layout-aware fuzzing for android drivers

With the commercialization of 5G mobile phones, Android drivers are increasing rapidly to utilize a large quantity of newly emerging feature-rich hardware. Most of these drivers are developed by third-party vendors and lack proper vulnerabilities review, posing a number of new potential risks to security and privacy. However, the complexity and diversity of Android drivers make the traditional analysis methods inefficient. For example, the driver-specific argument formats make traditional syscall fuzzers difficult to generate valid inputs, the pointer-heavy code makes static analysis results incomplete, and pointer casting hides the actual type. Triggering code deep in Android drivers remains challenging. We present CoLaFUZE, a coverage-guided and layout-aware fuzzing tool for automatically generating valid inputs and exploring the driver code. CoLaFUZE employs a kernel module to capture the data copy operation and redirect it to the fuzzing engine, ensuring that the correct size of the required data is transferred to the driver. CoLaFUZE leverages dynamic analysis and symbolic execution to recover the driver interfaces and generates valid inputs for the interfaces. Furthermore, the seed mutation module of CoLaFUZE leverages coverage information to achieve better seed quality and expose bugs deep in the driver. We evaluate CoLaFUZE on 5 modern Android mobile phones from the top vendors, including Google, Xiaomi, Samsung, Sony, and Huawei. The results show that CoLaFUZE can explore more code coverage compared with the state-of-the-art fuzzer, and CoLaFUZE successfully found 11 vulnerabilities in the testing devices. Copyright © 2021 The Institute of Electronics, Information and Communication Engineers.