Grant Hernandez (University of Florida), Marius Muench (Vrije Universiteit Amsterdam), Dominik Maier (TU Berlin), Alyssa Milburn (Vrije Universiteit Amsterdam), Shinjo Park (TU Berlin), Tobias Scharnowski (Ruhr-University Bochum), Tyler Tucker (University of Florida), Patrick Traynor (University of Florida), Kevin Butler (University of Florida)

Smartphones today leverage baseband processors to implement the multitude of cellular protocols. Basebands execute firmware, which is responsible for decoding hundreds of message types developed from three decades of cellular standards. Despite its large over-the-air attack surface, baseband firmware has received little security analysis. Previous work mostly analyzed
only a handful of firmware images from a few device models, but often relied heavily on time-consuming manual static analysis or single-function fuzzing.

To fill this gap, we present FirmWire, the first full-system emulation platform for baseband processors that executes unmodified baseband binary firmware. FirmWire provides baseband-specific APIs to easily add support for new vendors, firmware images, and security analyses. To demonstrate FirmWire’s scalability, we support 213 firmware images across 2 vendors and 9 phone models, allowing them to be executed and tested. With these images, FirmWire automatically discovers and bridges internal baseband APIs, allowing protocol messages to be injected with ease. Using these entry points, we selected the LTE and GSM protocols for fuzzing and discovered 7 pre-authentication memory corruptions that could lead to remote code execution--4 of which were previously unknown. We reproduced these crashes over-the-air on real devices, proving FirmWire’s emulation accuracy. FirmWire is a scalable platform for baseband security testing and we release it as open-source to the community for future research.

View More Papers

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 55 ) ) ) [post__not_in] => Array ( [0] => 8489 ) )

Demo #10: Hijacking Connected Vehicle Alexa Skills

Wenbo Ding (University at Buffalo), Long Cheng (Clemson University), Xianghang Mi (University of Science and Technology of China), Ziming Zhao (University at Buffalo) and Hongxin Hu (University at Buffalo)

Read More

Building the VPNalyzer System

Reethika Ramesh (University of Michigan), Leonid Evdokimov (Independent), Diwen Xue, Roya Ensafi (University of Michigan)

Read More

VPNInspector: Systematic Investigation of the VPN Ecosystem

Reethika Ramesh (University of Michigan), Leonid Evdokimov (Independent), Diwen Xue (University of Michigan), Roya Ensafi (University of Michigan)

Read More

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)