https://arxiv.org/abs/2510.03761 Skip to main content Cornell University We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate arxiv logo > cs > arXiv:2510.03761 [ ] Help | Advanced Search [All fields ] Search arXiv logo Cornell University Logo [ ] GO quick links * Login * Help Pages * About Computer Science > Cryptography and Security arXiv:2510.03761 (cs) [Submitted on 4 Oct 2025] Title:You Have Been LaTeXpOsEd: A Systematic Analysis of Information Leakage in Preprint Archives Using Large Language Models Authors:Richard A. Dubniczky, Bertalan Borsos, Tihanyi Norbert View a PDF of the paper titled You Have Been LaTeXpOsEd: A Systematic Analysis of Information Leakage in Preprint Archives Using Large Language Models, by Richard A. Dubniczky and 2 other authors View PDF HTML (experimental) Abstract:The widespread use of preprint repositories such as arXiv has accelerated the communication of scientific results but also introduced overlooked security risks. Beyond PDFs, these platforms provide unrestricted access to original source materials, including LaTeX sources, auxiliary code, figures, and embedded comments. In the absence of sanitization, submissions may disclose sensitive information that adversaries can harvest using open-source intelligence. In this work, we present the first large-scale security audit of preprint archives, analyzing more than 1.2 TB of source data from 100,000 arXiv submissions. We introduce LaTeXpOsEd, a four-stage framework that integrates pattern matching, logical filtering, traditional harvesting techniques, and large language models (LLMs) to uncover hidden disclosures within non-referenced files and LaTeX comments. To evaluate LLMs' secret-detection capabilities, we introduce LLMSec-DB, a benchmark on which we tested 25 state-of-the-art models. Our analysis uncovered thousands of PII leaks, GPS-tagged EXIF files, publicly available Google Drive and Dropbox folders, editable private SharePoint links, exposed GitHub and Google credentials, and cloud API keys. We also uncovered confidential author communications, internal disagreements, and conference submission credentials, exposing information that poses serious reputational risks to both researchers and institutions. We urge the research community and repository operators to take immediate action to close these hidden security gaps. To support open science, we release all scripts and methods from this study but withhold sensitive findings that could be misused, in line with ethical principles. The source code and related material are available at the project website this https URL Subjects: Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI) Cite as: arXiv:2510.03761 [cs.CR] (or arXiv:2510.03761v1 [cs.CR] for this version) https://doi.org/10.48550/arXiv.2510.03761 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Richard Dubniczky [view email] [v1] Sat, 4 Oct 2025 10:03:17 UTC (639 KB) Full-text links: Access Paper: View a PDF of the paper titled You Have Been LaTeXpOsEd: A Systematic Analysis of Information Leakage in Preprint Archives Using Large Language Models, by Richard A. Dubniczky and 2 other authors * View PDF * HTML (experimental) * TeX Source license icon view license Current browse context: cs.CR < prev | next > new | recent | 2025-10 Change to browse by: cs cs.AI References & Citations * NASA ADS * Google Scholar * Semantic Scholar export BibTeX citation Loading... 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