Inon Kaplan (Independent researcher), Ron even (Independent researcher), Amit Klein (The Hebrew University of Jerusalem, Israel)

This research is the first holistic analysis of the algorithmic security of the Google Fuchsia/gVisor network stack. Google Fuchsia is a new operating system developed by Google in a "clean slate" fashion. It is conjectured to eventually replace Android as an operating system for smartphones, tablets, and IoT devices. Fuchsia is already running in millions of Google Nest Hub consumer products. Google gVisor is an application kernel used by Google's App Engine, Cloud Functions, Cloud ML Engine, Cloud Run, and Google Kubernetes
Engine (GKE). Google Fuchsia uses the gVisor network stack code for its TCP/IP implementation.

We report multiple vulnerabilities in the algorithms used by Fuchsia/gVisor to populate network protocol header fields, specifically the TCP initial sequence number, TCP timestamp, TCP and UDP source ports, and IPv4/IPv6 fragment ID fields. In our holistic analysis, we show how a combination of multiple attacks results in the exposure of a PRNG seed and a hashing key used to generate the above fields. This enables an attacker to predict future values of the fields, which facilitates several network attacks. Our work focuses on web-based device tracking based on the stability and relative uniqueness of the PRNG seed and the hashing key. We demonstrate our device tracking techniques over the Internet with browsers running on multiple Fuchsia devices, in multiple browser modes (regular/privacy), and over multiple networks (including IPv4 vs. IPv6). Our tests verify that device tracking for Fuchsia is practical and yields a reliable device ID.

We conclude with recommendations on mitigating the attacks and their root causes. We reported our findings to Google, which issued CVEs and patches for the security vulnerabilities we disclosed.

View More Papers

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

Revisiting Physical-World Adversarial Attack on Traffic Sign Recognition: A...

Ningfei Wang (University of California, Irvine), Shaoyuan Xie (University of California, Irvine), Takami Sato (University of California, Irvine), Yunpeng Luo (University of California, Irvine), Kaidi Xu (Drexel University), Qi Alfred Chen (University of California, Irvine)

Read More

RContainer: A Secure Container Architecture through Extending ARM CCA...

Qihang Zhou (Institute of Information Engineering, Chinese Academy of Sciences), Wenzhuo Cao (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyberspace Security, University of Chinese Academy of Sciences), Xiaoqi Jia (Institute of Information Engineering, Chinese Academy of Sciences), Peng Liu (The Pennsylvania State University, USA), Shengzhi Zhang (Department of Computer Science, Metropolitan College,…

Read More

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