MODFuzz: A Multiobjective Directed Fuzzer for USB Drivers
USB interfaces have become ubiquitous in various Internet of Things (IoT) devices, all adhering to the same universal serial bus (USB) protocol. While enhancing convenience, they also widen the potential attack surface. Fuzzing is a proactive way to identify potential security threats for USB drivers. However, existing USB driver fuzzers primarily prioritize the code coverage of USB drivers, leading to a significant waste of computational resources on irrelevant code segments. To this end, we combine directed fuzzing and USB driver fuzzing for the first time, and present multiobjective directed fuzzer (MODFuzz), a pioneering multiobjective directed fuzzing method for USB drivers. MODFuzz autonomously locates the most vulnerable parts within USB drivers, concentrating fuzzing efforts on these areas. Diverging from the existing directed fuzzers, MODFuzz employs a dynamic direction instead of predetermined addresses to guide the fuzzing campaign toward the triggered execution traces with a greater probability of containing vulnerabilities. MODFuzz outperforms the strong baseline in terms of execution speed (about 14% improvement) and crash generation capabilities (about 69% improvement). Meanwhile, we found six previously unknown bugs (all confirmed and assigned vulnerability IDs) in Linux kernel v6.4.10 and received acknowledgment from Red Hat.
Authors
- Side Liu (ORCID: https://orcid.org/0009-0003-8106-4101)
- Yilin Zhou (ORCID: https://orcid.org/0009-0005-2952-5198)
- Jianming Fu (ORCID: https://orcid.org/0000-0002-4639-5824)
- Guojun Peng (ORCID: https://orcid.org/0000-0001-5731-8958)
- Chenyang Wang (ORCID: https://orcid.org/0009-0003-8898-2431)
- Zhen Li (ORCID: https://orcid.org/0000-0001-5195-8962)
- Yanhao Wang (ORCID: https://orcid.org/0000-0002-6990-2972)
- Xingliang Wang (ORCID: https://orcid.org/0000-0003-2843-4831)
- Xiuzhang Yang
Institutions
- Ministry of Public Security of the People's Republic of China (CN)
- Guizhou University (CN)
- Wuhan University (CN)
- Bloomington Health Foundation (US)
- Indiana University Bloomington (US)
- Guizhou Academy of Sciences (CN)
Publication Details
- Journal
- IEEE Internet of Things Journal
- Published
- 2025-02-28
- DOI
- https://doi.org/10.1109/jiot.2025.3546664
- Primary Topic
- Video Analysis and Summarization
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China