Xigao Li (Stony Brook University), Anurag Yepuri (Stony Brook University), Nick Nikiforakis (Stony Brook University)

As cryptocurrencies increase in popularity and users obtain and manage their own assets, attackers are pivoting from just abusing cryptocurrencies as a payment mechanism, to stealing crypto assets from end users. In this paper, we report on the first large-scale analysis of cryptocurrency giveaway scams. Giveaway scams are deceptively simple scams where attackers set up webpages advertising fake events and promising users to double or triple the funds that they send to a specific wallet address. To understand the population of these scams in the wild we design and implement CryptoScamTracker, a tool that uses Certificate Transparency logs to identify likely giveaway scams. Through a 6-month-long experiment, CryptoScamTracker identified a total of 10,079 giveaway scam websites targeting users of all popular cryptocurrencies. Next to analyzing the hosting and domain preferences of giveaway scammers, we perform the first quantitative analysis of stolen funds using the public blockchains of the abused cryptocurrencies, extracting the transactions corresponding to 2,266 wallets belonging to scammers. We find that just for the scams discovered in our reporting period, attackers have stolen the equivalent of tens of millions of dollars, organizing large-scale campaigns across different cryptocurrencies. Lastly, we find evidence that attackers try to re-victimize users by offering fund-recovery services and that some victims send funds multiple times to the same scammers.

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Hope of Delivery: Extracting User Locations From Mobile Instant...

Theodor Schnitzler (Research Center Trustworthy Data Science and Security, TU Dortmund, and Ruhr-Universität Bochum), Katharina Kohls (Radboud University), Evangelos Bitsikas (Northeastern University and New York University Abu Dhabi), Christina Pöpper (New York University Abu Dhabi)

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Anomaly Detection in the Open World: Normality Shift Detection,...

Dongqi Han (Tsinghua University), Zhiliang Wang (Tsinghua University), Wenqi Chen (Tsinghua University), Kai Wang (Tsinghua University), Rui Yu (Tsinghua University), Su Wang (Tsinghua University), Han Zhang (Tsinghua University), Zhihua Wang (State Grid Shanghai Municipal Electric Power Company), Minghui Jin (State Grid Shanghai Municipal Electric Power Company), Jiahai Yang (Tsinghua University), Xingang Shi (Tsinghua University), Xia…

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dewolf: Improving Decompilation by leveraging User Surveys

Steffen Enders, Eva-Maria C. Behner, Niklas Bergmann, Mariia Rybalka, Elmar Padilla (Fraunhofer FKIE, Germany), Er Xue Hui, Henry Low, Nicholas Sim (DSO National Laboratories, Singapore)

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