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

Retrofitting XoM for Stripped Binaries without Embedded Data Relocation

Chenke Luo (Wuhan University), Jiang Ming (Tulane University), Mengfei Xie (Wuhan University), Guojun Peng (Wuhan University), Jianming Fu (Wuhan University)

Read More

Can a Cybersecurity Question Answering Assistant Help Change User...

Lea Duesterwald (Carnegie Mellon University), Ian Yang (Carnegie Mellon University), Norman Sadeh (Carnegie Mellon University)

Read More

Victim-Centred Abuse Investigations and Defenses for Social Media Platforms

Zaid Hakami (Florida International University and Jazan University), Ashfaq Ali Shafin (Florida International University), Peter J. Clarke (Florida International University), Niki Pissinou (Florida International University), and Bogdan Carbunar (Florida International University)

Read More

mmProcess: Phase-Based Speech Reconstruction from mmWave Radar

Hyeongjun Choi, Young Eun Kwon, Ji Won Yoon (Korea University)

Read More