Shushang Wen (School of Cyber Science and Technology, University of Science and Technology of China), Yiming Zhang (Tsinghua University), Yuxiang Shen (School of Cyber Science and Technology, University of Science and Technology of China), Bingyu Li (School of Cyber Science and Technology, Beihang University), Haixin Duan (Tsinghua University; Zhongguancun Laboratory), Jingqiang Lin (School of Cyber Science and Technology, University of Science and Technology of China)

Email clients that support auto-configuration mechanisms automatically retrieve server configuration information, such as the hostname, port number, and connection type, allowing users to log in by simply entering email addresses and passwords. Auto-configuration mechanisms are being increasingly adopted. However, the security implications of these mechanisms, both in terms of implementation and deployment, have not yet been thoroughly studied. In this paper, we present the first systematic analysis of security threats associated with email auto-configuration and evaluate their impacts. We summarize 10 attack scenarios, covering 17 defects (including 8 newly identified ones), along with 4 inadequate client UI notifications. These attack scenarios can either cause a victim to connect to an attacker-controlled server or establish an insecure connection, putting the victim’s credentials at risk. Moreover, our large-scale measurements and in-depth analysis revealed serious insecurity of auto-configuration applications in the wild. On the server-side, we discovered 49,013 domains, including 19 of the Top-1K popular domains, were misconfigured. On the client-side, 22 out of 29 clients were vulnerable to those threats. Moreover, 27 out of 29 clients exhibited at least one UI-notification defect that facilitates silent attacks. These defects arise from misconfiguration, mismanagement, flawed implementation and compatibility. We hope this paper raises attention to email auto-configuration security.

View More Papers

Be Careful of What You Embed: Demystifying OLE Vulnerabilities

Yunpeng Tian (Huazhong University of Science and Technology), Feng Dong (Huazhong University of Science and Technology), Haoyi Liu (Huazhong University of Science and Technology), Meng Xu (University of Waterloo), Zhiniang Peng (Huazhong University of Science and Technology; Sangfor Technologies Inc.), Zesen Ye (Sangfor Technologies Inc.), Shenghui Li (Huazhong University of Science and Technology), Xiapu Luo…

Read More

Was This You? Investigating the Design Considerations for Suspicious...

Sena Sahin (Georgia Institute of Technology), Burak Sahin (Georgia Institute of Technology), Frank Li (Georgia Institute of Technology)

Read More

The Forking Way: When TEEs Meet Consensus

Annika Wilde (Ruhr University Bochum), Tim Niklas Gruel (Ruhr University Bochum), Claudio Soriente (NEC Laboratories Europe), Ghassan Karame (Ruhr University Bochum)

Read More

A New PPML Paradigm for Quantized Models

Tianpei Lu (The State Key Laboratory of Blockchain and Data Security, Zhejiang University), Bingsheng Zhang (The State Key Laboratory of Blockchain and Data Security, Zhejiang University), Xiaoyuan Zhang (The State Key Laboratory of Blockchain and Data Security, Zhejiang University), Kui Ren (The State Key Laboratory of Blockchain and Data Security, Zhejiang University)

Read More