Kevin van Liebergen (IMDEA Software Institute), Gibran Gomez (IMDEA Software Institute), Srdjan Matic (IMDEA Software Institute), Juan Caballero (IMDEA Software Institute)

We present the first systematic study of database ransom(ware) attacks, a class of attacks where attackers scan for database servers, log in by leveraging the lack of authentication or weak credentials, drop the database contents, and demand a ransom to return the deleted data. We examine 23,736 ransom notes collected from 60,427 compromised database servers over three years, and set up database honeypots to obtain a first-hand view of current attacks. Database ransom(ware) attacks are prevalent with 6K newly infected servers in March 2024, a 60% increase over a year earlier. Our honeypots get infected in 14 hours since they are connected to the Internet. Weak authentication issues are two orders of magnitude more frequent on Elasticsearch servers compared to MySQL servers due to slow adoption of the latest Elasticsearch versions. To analyze who is behind database ransom(ware) attacks we implement a clustering approach that first identifies campaigns using the similarity of the ransom notes text. Then, it determines which campaigns are run by the same group by leveraging indicator reuse and information from the Bitcoin blockchain. For each group, it computes properties such as the number of compromised servers, the lifetime, the revenue, and the indicators used. Our approach identifies that the 60,427 database servers are victims of 91 campaigns run by 32 groups. It uncovers a dominant group responsible for 76% of the infected servers and 90% of the financial impact. We find links between the dominant group, a nation-state, and a previous attack on Git repositories.

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Philipp Mackensen (Ruhr University Bochum), Paul Staat (Max Planck Institute for Security and Privacy), Stefan Roth (Ruhr University Bochum), Aydin Sezgin (Ruhr University Bochum), Christof Paar (Max Planck Institute for Security and Privacy), Veelasha Moonsamy (Ruhr University Bochum)

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Marzieh Bitaab (Arizona State University), Alireza Karimi (Arizona State University), Zhuoer Lyu (Arizona State University), Adam Oest (Amazon), Dhruv Kuchhal (Amazon), Muhammad Saad (X Corp.), Gail-Joon Ahn (Arizona State University), Ruoyu Wang (Arizona State University), Tiffany Bao (Arizona State University), Yan Shoshitaishvili (Arizona State University), Adam Doupé (Arizona State University)

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Moneta: Ex-Vivo GPU Driver Fuzzing by Recalling In-Vivo Execution...

Joonkyo Jung (Department of Computer Science, Yonsei University), Jisoo Jang (Department of Computer Science, Yonsei University), Yongwan Jo (Department of Computer Science, Yonsei University), Jonas Vinck (DistriNet, KU Leuven), Alexios Voulimeneas (CYS, TU Delft), Stijn Volckaert (DistriNet, KU Leuven), Dokyung Song (Department of Computer Science, Yonsei University)

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Generating API Parameter Security Rules with LLM for API...

Jinghua Liu (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China; School of Cyber Security, University of Chinese Academy of Sciences, China), Yi Yang (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China; School of Cyber Security, University of Chinese Academy of Sciences, China), Kai Chen (Institute of Information Engineering, Chinese Academy of…

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