FirmHunter: State-Aware and Introspection-Driven Grey-Box Fuzzing towards IoT Firmware

IoT devices are exponentially increasing in all aspects of our lives. Via the web interfaces of IoT devices, attackers can control IoT devices by exploiting their vulnerabilities. In order to guarantee IoT security, testing these IoT devices to detect vulnerabilities is very important. In this work,...

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Bibliographic Details
Main Authors: Qidi Yin, Xu Zhou, Hangwei Zhang
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/11/19/9094
Description
Summary:IoT devices are exponentially increasing in all aspects of our lives. Via the web interfaces of IoT devices, attackers can control IoT devices by exploiting their vulnerabilities. In order to guarantee IoT security, testing these IoT devices to detect vulnerabilities is very important. In this work, we present FirmHunter, an automated state-aware and introspection-driven grey-box fuzzer towards Linux-based firmware images on the basis of emulation. It employs a message-state queue to overcome the dependency problem in test cases. Furthermore, it implements a scheduler collecting execution information from system introspection to drive fuzzing towards more interesting test cases, which speeds up vulnerability discovery. We evaluate FirmHunter by emulating and fuzzing eight firmware images including seven routers and one IP camera with a state-of-the-art IoT fuzzer FirmFuzz and a web application scanner ZAP. Our evaluation results show that (1) the message-state queue enables FirmHunter to parse the dependencies in test cases and find real-world vulnerabilities that other fuzzers cannot detect; (2) our scheduler accelerates the discovery of vulnerabilities by an average of 42%; and (3) FirmHunter is able to find unknown vulnerabilities.
ISSN:2076-3417