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)

Online scams have become a top threat for Internet users, inflicting $10 billion in losses in 2023 only in the US. Prior work has studied specific scam types, but no work has compared different scam types. In this work, we perform what we believe is the first study of the exposure of end users to different types of online scams. We examine seven popular scam types: shopping, financial, cryptocurrency, gambling, dating, funds recovery, and employment scams. To quantify end-user exposure, we search for observations of 607K scam domains over a period of several months by millions of desktop and mobile devices belonging to customers of a large cybersecurity vendor. We classify the scam domains into the seven scam types and measure for each scam type the exposure of end users, geographical variations, scam domain lifetime, and the promotion of scam websites through online advertisements.

We examine 25.1M IP addresses accessing over 414K scam domains. On a daily basis, 149K devices are exposed to online scams, with an average of 101K (0.8%) of desktop devices being exposed compared to 48K (0.3%) of mobile devices. Shopping scams are the most prevalent scam type, being observed by a total of 10.2M IPs, followed by cryptocurrency scams, observed by 653K IPs. After being observed in the telemetry, the scam domains remain alive for a median of 11 days. In at least 9.2M (13.3%) of all scam observations users followed an advertisement. These ads are largely (59%) hosted on social media, with Facebook being the preferred source.

View More Papers

YuraScanner: Leveraging LLMs for Task-driven Web App Scanning

Aleksei Stafeev (CISPA Helmholtz Center for Information Security), Tim Recktenwald (CISPA Helmholtz Center for Information Security), Gianluca De Stefano (CISPA Helmholtz Center for Information Security), Soheil Khodayari (CISPA Helmholtz Center for Information Security), Giancarlo Pellegrino (CISPA Helmholtz Center for Information Security)

Read More

Rethinking Trust in Forge-Based Git Security

Aditya Sirish A Yelgundhalli (New York University), Patrick Zielinski (New York University), Reza Curtmola (New Jersey Institute of Technology), Justin Cappos (New York University)

Read More

The Discriminative Power of Cross-layer RTTs in Fingerprinting Proxy...

Diwen Xue (University of Michigan), Robert Stanley (University of Michigan), Piyush Kumar (University of Michigan), Roya Ensafi (University of Michigan)

Read More

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