Mengying Wu (Fudan University), Geng Hong (Fudan University), Jinsong Chen (Fudan University), Qi Liu (Fudan University), Shujun Tang (QI-ANXIN Technology Research Institute; Tsinghua University), Youhao Li (QI-ANXIN Technology Research Institute), Baojun Liu (Tsinghua University), Haixin Duan (Tsinghua University; Quancheng Laboratory), Min Yang (Fudan University)

In the digital age, device search engines such as Censys and Shodan play crucial roles by scanning the internet to catalog online devices, aiding in the understanding and mitigation of network security risks. While previous research has used these tools to detect devices and assess vulnerabilities, there remains uncertainty regarding the assets they scan, the strategies they employ, and whether they adhere to ethical guidelines.

This study presents the first comprehensive examination of these engines’ operational and ethical dimensions. We developed a novel framework to trace the IP addresses utilized by these engines and collected 1,407 scanner IPs. By uncovering their IPs, we gain deep insights into the actions of device search engines for the first time and gain original findings. By employing 28 honeypots to monitor their scanning activities extensively in one year, we demonstrate that users can hardly evade scans by blocklisting scanner IPs or migrating service ports. Our findings reveal significant ethical concerns, including a lack of transparency, harmlessness, and anonymity. Notably, these engines often fail to provide transparency and do not allow users to opt out of scans. Further, the engines send malformed requests, attempt to access excessive details without authorization, and even publish personally identifiable information(PII) and screenshots on search results. These practices compromise user privacy and expose devices to further risks by potentially aiding malicious entities. This paper emphasizes the urgent need for stricter ethical standards and enhanced transparency in the operations of device search engines, offering crucial insights into safeguarding against invasive scanning practices and protecting digital infrastructures.

View More Papers

On the Robustness of LDP Protocols for Numerical Attributes...

Xiaoguang Li (Xidian University, Purdue University), Zitao Li (Alibaba Group (U.S.) Inc.), Ninghui Li (Purdue University), Wenhai Sun (Purdue University, West Lafayette, USA)

Read More

Automated Expansion of Privacy Data Taxonomy for Compliant Data...

Yue Qin (Indiana University Bloomington & Central University of Finance and Economics), Yue Xiao (Indiana University Bloomington & IBM Research), Xiaojing Liao (Indiana University Bloomington)

Read More

PQConnect: Automated Post-Quantum End-to-End Tunnels

Daniel J. Bernstein (University of Illinois at Chicago and Academia Sinica), Tanja Lange (Eindhoven University of Technology amd Academia Sinica), Jonathan Levin (Academia Sinica and Eindhoven University of Technology), Bo-Yin Yang (Academia Sinica)

Read More

A Large-Scale Measurement Study of the PROXY Protocol and...

Stijn Pletinckx (University of California, Santa Barbara), Christopher Kruegel (University of California, Santa Barbara), Giovanni Vigna (University of California, Santa Barbara)

Read More