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

Towards LLM-Assisted Vulnerability Detection and Repair for Open-Source 5G...

Rupam Patir (University at Buffalo), Qiqing Huang (University at Buffalo), Keyan Guo (University at Buffalo), Wanda Guo (Texas A&M University), Guofei Gu (Texas A&M University), Haipeng Cai (University at Buffalo), Hongxin Hu (University at Buffalo)

Read More

Secure Transformer Inference Made Non-interactive

Jiawen Zhang (Zhejiang University), Xinpeng Yang (Zhejiang University), Lipeng He (University of Waterloo), Kejia Chen (Zhejiang University), Wen-jie Lu (Zhejiang University), Yinghao Wang (Zhejiang University), Xiaoyang Hou (Zhejiang University), Jian Liu (Zhejiang University), Kui Ren (Zhejiang University), Xiaohu Yang (Zhejiang University)

Read More

The Philosopher’s Stone: Trojaning Plugins of Large Language Models

Tian Dong (Shanghai Jiao Tong University), Minhui Xue (CSIRO's Data61), Guoxing Chen (Shanghai Jiao Tong University), Rayne Holland (CSIRO's Data61), Yan Meng (Shanghai Jiao Tong University), Shaofeng Li (Southeast University), Zhen Liu (Shanghai Jiao Tong University), Haojin Zhu (Shanghai Jiao Tong University)

Read More

OrbID: Identifying Orbcomm Satellite RF Fingerprints

Cédric Solenthaler (ETH Zurich), Joshua Smailes (University of Oxford), Martin Strohmeier (armasuisse Science & Technology)

Read More