Sayak Saha Roy, Unique Karanjit, Shirin Nilizadeh (The University of Texas at Arlington)

Twitter maintains a blackbox approach for detecting malicious URLs shared on its platform. In this study, we evaluate the efficiency of their detection mechanism against newer phishing and drive-by download threats posted on the website over three different time periods of the year. Our findings indicate that several threats remained undetected by Twitter, with the majority of them originating from nine different free website hosting services. These URLs targeted 19 popular organizations and also distributed malicious files from 9 different threat categories. Moreover, the malicious websites hosted under these services were also less likely to get detected by URL scanning tools than other similar threats hosted elsewhere, and were accessible on their respective domains for a much longer duration. We believe that the aforementioned features, combined with the ease of access (drag and drop website creating interface, up-to-date SSL certification, reputed domain, etc.) provides attackers a fast and convenient way to create malicious attacks using these services. On the other hand, we also observed that the majority of the URLs which were actually detected by Twitter remained active on the platform throughout our study, allowing them to be easily distributed across the platform. Also, several benign websites in our dataset were detected by Twitter as being malicious. We hypothesize that this is caused due to a blocklisting procedure used by Twitter, which detects all URLs originating from certain domains, irrespective of their content. Thus, our results identify a family of potent threats, which are distributed freely on Twitter, and are also not detected by the majority of URL scanning tools, or even the services which host them, thus making the need for a more thorough URL blocking approach from Twitter’s end more apparent.

View More Papers

Does Every Second Count? Time-based Evolution of Malware Behavior...

Alexander Küchler (Fraunhofer AISEC), Alessandro Mantovani (EURECOM), Yufei Han (NortonLifeLock Research Group), Leyla Bilge (NortonLifeLock Research Group), Davide Balzarotti (EURECOM)

Read More

C^2SR: Cybercrime Scene Reconstruction for Post-mortem Forensic Analysis

Yonghwi Kwon (University of Virginia), Weihang Wang (University at Buffalo, SUNY), Jinho Jung (Georgia Institute of Technology), Kyu Hyung Lee (University of Georgia), Roberto Perdisci (Georgia Institute of Technology and University of Georgia)

Read More

Obfuscated Access and Search Patterns in Searchable Encryption

Zhiwei Shang (University of Waterloo), Simon Oya (University of Waterloo), Andreas Peter (University of Twente), Florian Kerschbaum (University of Waterloo)

Read More