Ziqiang Wang (Southeast University), Xuewei Feng (Tsinghua University), Qi Li (Tsinghua University), Kun Sun (George Mason University), Yuxiang Yang (Tsinghua University), Mengyuan Li (University of Toronto), Ganqiu Du (China Software Testing Center), Ke Xu (Tsinghua University), Jianping Wu (Tsinghua University)

In this paper, we unveil a fundamental side channel in Wi-Fi networks, specifically the observable frame size, which can be exploited by attackers to conduct TCP hijacking attacks.

Despite the various security mechanisms (e.g., WEP and WPA2/WPA3) implemented to safeguard Wi-Fi networks, our study reveals that an off-path attacker can still extract sufficient information from the frame size side channel to hijack the victim's TCP connection.

Our side channel attack is based on two significant findings: (i) response packets (e.g., ACK and RST) generated by TCP receivers vary in size, and (ii) the encrypted frames containing these response packets have consistent and distinguishable sizes.

By observing the size of the victim's encrypted frames, the attacker can detect and hijack the victim's TCP connections.

We validate the effectiveness of this side channel attack through two case studies, i.e., SSH DoS and web traffic manipulation.

Precisely, our attack can terminate the victim's SSH session in 19 seconds and inject malicious data into the victim's web traffic within 28 seconds.

Furthermore, we conduct extensive measurements to evaluate the impact of our attack on real-world Wi-Fi networks. We test 30 popular wireless routers from 9 well-known vendors, and none of these routers can protect victims from our attack. Besides, we implement our attack in 80 real-world Wi-Fi networks and successfully hijack the victim's TCP connections in 75 (93.75%) evaluated Wi-Fi networks.

We have responsibly disclosed the vulnerability to the Wi-Fi Alliance and proposed several mitigation strategies to address this issue.

View More Papers

Understanding Miniapp Malware: Identification, Dissection, and Characterization

Yuqing Yang (The Ohio State University), Yue Zhang (Drexel University), Zhiqiang Lin (The Ohio State University)

Read More

Ctrl+Alt+Deceive: Quantifying User Exposure to Online Scams

Platon Kotzias (Norton Research Group, BforeAI), Michalis Pachilakis (Norton Research Group, Computer Science Department University of Crete), Javier Aldana Iuit (Norton Research Group), Juan Caballero (IMDEA Software Institute), Iskander Sanchez-Rola (Norton Research Group), Leyla Bilge (Norton Research Group)

Read More

Rethink Custom Transformers for Binary Analysis

Heng Yin, Professor, Department of Computer Science and Engineering, University of California, Riverside

Read More

Towards Anonymous Chatbots with (Un)Trustworthy Browser Proxies

Dzung Pham, Jade Sheffey, Chau Minh Pham, and Amir Houmansadr (University of Massachusetts Amherst)

Read More