Eunsoo Kim (KAIST), Dongkwan Kim (KAIST), CheolJun Park (KAIST), Insu Yun (KAIST), Yongdae Kim (KAIST)

Cellular basebands play a crucial role in mobile communication. However, it is significantly challenging to assess their security for several reasons. Manual analysis is inevitable because of the obscurity and complexity of baseband firmware; however, such analysis requires repetitive efforts to cover diverse models or versions. Automating the analysis is also non-trivial because the firmware is significantly large and contains numerous functions associated with complex cellular protocols. Therefore, existing approaches on baseband analysis are limited to only a couple of models or versions within a single vendor. In this paper, we propose a novel approach named BaseSpec, which performs a comparative analysis of baseband software and cellular specifications. By leveraging the standardized message structures in the specification, BaseSpec inspects the message structures implemented in the baseband software systematically. It requires a manual yet one-time analysis effort to determine how the message structures are embedded in target firmware. Then, BaseSpec compares the extracted message structures with those in the specification syntactically and semantically, and finally, it reports mismatches. These mismatches indicate the developer mistakes, which break the compliance of the baseband with the specification, or they imply potential vulnerabilities. We evaluated BaseSpec with 18 baseband firmware images of 9 models from one of the top three vendors and found hundreds of mismatches. By analyzing these mismatches, we discovered 9 erroneous cases: 5 functional errors and 4 memory-related vulnerabilities. Notably, two of these are critical remote code execution 0-days. Moreover, we applied BaseSpec to 3 models from another vendor, and BaseSpec found multiple mismatches, two of which led us to discover a buffer overflow bug.

View More Papers

Model-Agnostic Defense for Lane Detection against Adversarial Attack

Henry Xu, An Ju, and David Wagner (UC Berkeley) Baidu Security Auto-Driving Security Award Winner ($1000 cash prize)!

Read More

A Devil of a Time: How Vulnerable is NTP...

Yarin Perry (The Hebrew University of Jerusalem), Neta Rozen-Schiff (The Hebrew University of Jerusalem), Michael Schapira (The Hebrew University of Jerusalem)

Read More

ALchemist: Fusing Application and Audit Logs for Precise Attack...

Le Yu (Purdue University), Shiqing Ma (Rutgers University), Zhuo Zhang (Purdue University), Guanhong Tao (Purdue University), Xiangyu Zhang (Purdue University), Dongyan Xu (Purdue University), Vincent E. Urias (Sandia National Laboratories), Han Wei Lin (Sandia National Laboratories), Gabriela Ciocarlie (SRI International), Vinod Yegneswaran (SRI International), Ashish Gehani (SRI International)

Read More

Digital Technologies in Pandemic: The Good, the Bad and...

Moderator: Ahmad-Reza Sadeghi, TU Darmstadt, Germany Panelists: Mario Guglielmetti, Legal Officer, European Data Protection Supervisor* Jaap-Henk Hoepman, Radbaud University, The Netherlands Alexandra Dmitrienko, University of Würzburg, Germany, Farinaz Koushanfar, UCSD, USA *attending in his personal capacity

Read More