Leon Trampert (CISPA Helmholtz Center for Information Security), Daniel Weber (CISPA Helmholtz Center for Information Security), Lukas Gerlach (CISPA Helmholtz Center for Information Security), Christian Rossow (CISPA Helmholtz Center for Information Security), Michael Schwarz (CISPA Helmholtz Center for Information Security)

In an attempt to combat user tracking, both privacy-aware browsers (e.g., Tor) and email applications usually disable JavaScript. This effectively closes a major angle for user fingerprinting.
However, recent findings hint at the potential for privacy leakage through selected Cascading Style Sheets (CSS) features. Nevertheless, the full fingerprinting potential of CSS remains unknown, and it is unclear if attacks apply to more restrictive settings such as email.

In this paper, we systematically investigate the modern dynamic features of CSS and their applicability for script-less fingerprinting, bypassing many state-of-the-art mitigations. We present three innovative techniques based on fuzzing and templating that exploit nuances in CSS container queries, arithmetic functions, and complex selectors. This allows us to infer detailed application, OS, and hardware configurations at high accuracy. For browsers, we can distinguish 97.95% of 1176 tested browser-OS combinations. Our methods also apply to email applications - as shown for 8 out of 21 tested web, desktop or mobile email applications. This demonstrates that fingerprinting is possible in the highly restrictive setting of HTML emails and expands the scope of tracking beyond traditional web environments.

In response to these and potential future CSS-based tracking capabilities, we propose two defense mechanisms that eliminate the root causes of privacy leakage. For browsers, we propose to preload conditional resources, which eliminates feature-dependent leakage. For the email setting, we design an email proxy service that retains privacy and email integrity while largely preserving feature compatibility. Our work provides new insights and solutions to the ongoing privacy debate, highlighting the importance of robust defenses against emerging tracking methods.

View More Papers

VoiceRadar: Voice Deepfake Detection using Micro-Frequency and Compositional Analysis

Kavita Kumari (Technical University of Darmstadt), Maryam Abbasihafshejani (University of Texas at San Antonio), Alessandro Pegoraro (Technical University of Darmstadt), Phillip Rieger (Technical University of Darmstadt), Kamyar Arshi (Technical University of Darmstadt), Murtuza Jadliwala (University of Texas at San Antonio), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

Read More

The Midas Touch: Triggering the Capability of LLMs for...

Yi Yang (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China; School of Cyber Security, University of Chinese Academy of Sciences, China), Jinghua Liu (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China; School of Cyber Security, University of Chinese Academy of Sciences, China), Kai Chen (Institute of Information Engineering, Chinese Academy of…

Read More

PowerRadio: Manipulate Sensor Measurement via Power GND Radiation

Yan Jiang (Zhejiang University), Xiaoyu Ji (Zhejiang University), Yancheng Jiang (Zhejiang University), Kai Wang (Zhejiang University), Chenren Xu (Peking University), Wenyuan Xu (Zhejiang University)

Read More

MOBIDOJO: A Virtual Security Combat Platform for 5G Cellular...

Hyunwoo Lee (Ohio State University), Haohuang Wen (Ohio State University), Phillip Porras (SRI), Vinod Yegneswaran (SRI), Ashish Gehani (SRI), Prakhar Sharma (SRI), Zhiqiang Lin (Ohio State University)

Read More