Michael Meli (North Carolina State University), Matthew R. McNiece (Cisco Systems and North Carolina State University), Bradley Reaves (North Carolina State University)

GitHub and similar platforms have made public collaborative development of software commonplace. However, a problem arises when this public code must manage authentication secrets, such as API keys or cryptographic secrets. These secrets must be kept private for security, yet common development practices like adding these secrets to code make accidental leakage frequent. In this paper, we present the first large-scale and longitudinal analysis of secret leakage on GitHub. We examine billions of files collected using two complementary approaches: a nearly six-month scan of real-time public GitHub commits and a public snapshot covering 13% of open-source repositories. We focus on private key files and 11 high-impact platforms with distinctive API key formats. This focus allows us to develop conservative detection techniques that we manually and automatically evaluate to ensure accurate results. We find that not only is secret leakage pervasive — affecting over 100,000 repositories— but that thousands of new, unique secrets are leaked every day. We also use our data to explore possible root causes of leakage and to evaluate potential mitigation strategies. This work shows that secret leakage on public repository platforms is rampant and far from a solved problem, placing developers and services at persistent risk of compromise and abuse.

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PeriScope: An Effective Probing and Fuzzing Framework for the...

Dokyung Song (University of California, Irvine), Felicitas Hetzelt (Technical University of Berlin), Dipanjan Das (University of California, Santa Barbara), Chad Spensky (University of California, Santa Barbara), Yeoul Na (University of California, Irvine), Stijn Volckaert (University of California, Irvine and KU Leuven), Giovanni Vigna (University of California, Santa Barbara), Christopher Kruegel (University of California, Santa Barbara),…

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ML-Leaks: Model and Data Independent Membership Inference Attacks and...

Ahmed Salem (CISPA Helmholtz Center for Information Security), Yang Zhang (CISPA Helmholtz Center for Information Security), Mathias Humbert (Swiss Data Science Center, ETH Zurich/EPFL), Pascal Berrang (CISPA Helmholtz Center for Information Security), Mario Fritz (CISPA Helmholtz Center for Information Security), Michael Backes (CISPA Helmholtz Center for Information Security)

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JavaScript Template Attacks: Automatically Inferring Host Information for Targeted...

Michael Schwarz (Graz University of Technology), Florian Lackner (Graz University of Technology), Daniel Gruss (Graz University of Technology)

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Sereum: Protecting Existing Smart Contracts Against Re-Entrancy Attacks

Michael Rodler (University of Duisburg-Essen), Wenting Li (NEC Laboratories, Germany), Ghassan O. Karame (NEC Laboratories, Germany), Lucas Davi (University of Duisburg-Essen)

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