FirmUp

Author:

David Yaniv1,Partush Nimrod1,Yahav Eran1

Affiliation:

1. Technion, Haifa, Israel

Abstract

We present a static, precise, and scalable technique for finding CVEs (Common Vulnerabilities and Exposures) in stripped firmware images. Our technique is able to efficiently find vulnerabilities in real-world firmware with high accuracy. Given a vulnerable procedure in an executable binary and a firmware image containing multiple stripped binaries, our goal is to detect possible occurrences of the vulnerable procedure in the firmware image. Due to the variety of architectures and unique tool chains used by vendors, as well as the highly customized nature of firmware, identifying procedures in stripped firmware is extremely challenging. Vulnerability detection requires not only pairwise similarity between procedures but also information about the relationships between procedures in the surrounding executable. This observation serves as the foundation for a novel technique that establishes a partial correspondence between procedures in the two binaries. We implemented our technique in a tool called FirmUp and performed an extensive evaluation over 40 million procedures, over 4 different prevalent architectures, crawled from public vendor firmware images. We discovered 373 vulnerabilities affecting publicly available firmware, 147 of them in the latest available firmware version for the device. A thorough comparison of FirmUp to previous methods shows that it accurately and effectively finds vulnerabilities in firmware, while outperforming the detection rate of the state of the art by 45% on average.

Funder

European Union's Seventh Framework Programme

Israel Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Software

Cited by 35 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A cosine similarity-based labeling technique for vulnerability type detection using source codes;Computers & Security;2024-11

2. CEBin: A Cost-Effective Framework for Large-Scale Binary Code Similarity Detection;Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis;2024-09-11

3. Vulnerabilities and Security Patches Detection in OSS: A Survey;ACM Computing Surveys;2024-09-09

4. A Semantics-Based Approach on Binary Function Similarity Detection;IEEE Internet of Things Journal;2024-08-01

5. CodeExtract: Enhancing Binary Code Similarity Detection with Code Extraction Techniques;Proceedings of the 25th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems;2024-06-20

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