CyberIntel ⬡ News
★ Saved ◆ Cyber Reads
← Back ◬ AI & Machine Learning Apr 24, 2026

Hidden Secrets in the arXiv: Discovering, Analyzing, and Preventing Unintentional Information Disclosure in Source Files of Scientific Preprints

arXiv Security Archived Apr 24, 2026 ✓ Full text saved

arXiv:2604.20927v1 Announce Type: new Abstract: Preprints are essential for the timely and open dissemination of research. arXiv, the most widely used preprint service, takes the idea of open science one step further by not only publishing the actual preprints but also LaTeX sources and other files used to create them. As known from other contexts, such as GitHub repositories, and anecdotally exemplified for arXiv, making source code publicly available risks disclosing otherwise "hidden" informa

Full text archived locally
✦ AI Summary · Claude Sonnet


    Computer Science > Cryptography and Security [Submitted on 22 Apr 2026] Hidden Secrets in the arXiv: Discovering, Analyzing, and Preventing Unintentional Information Disclosure in Source Files of Scientific Preprints Jan Pennekamp, Johannes Lohmöller, David Schütte, Joscha Loos, Martin Henze Preprints are essential for the timely and open dissemination of research. arXiv, the most widely used preprint service, takes the idea of open science one step further by not only publishing the actual preprints but also LaTeX sources and other files used to create them. As known from other contexts, such as GitHub repositories, and anecdotally exemplified for arXiv, making source code publicly available risks disclosing otherwise "hidden" information. Consequently, the public availability of paper sources raises the question of how much sensitive content is (unintentionally) disclosed through them. In this paper, we systematically answer this question for all 2.7M arXiv submissions with available source files across three dimensions of source file-induced information disclosure: (1) inclusion of unnecessary files, (2) metadata embedded in files, and (3) irrelevant content in files such as source code comments. Our analysis reveals that nearly every arXiv submission contains some form of "hidden" information. Notable findings range from links to editable web documents for internal coordination over API and private keys to complete Git histories. While different tools promise to remove such information from source files, we show that they fail to reliably achieve the intended cleaning functionality. To mitigate this situation, we provide ALC-NG to comprehensively remove files, metadata, and comments that are not needed to compile a LaTeX paper. Comments: 20 pages, accepted at 47th IEEE Symposium on Security and Privacy (SP '26) Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2604.20927 [cs.CR]   (or arXiv:2604.20927v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2604.20927 Focus to learn more Submission history From: Jan Pennekamp [view email] [v1] Wed, 22 Apr 2026 08:18:10 UTC (451 KB) Access Paper: view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-04 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
    💬 Team Notes
    Article Info
    Source
    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    Apr 24, 2026
    Archived
    Apr 24, 2026
    Full Text
    ✓ Saved locally
    Open Original ↗