Devilray: A Systematic Adversarial Model Revealing Blind Spots in Fake Base Station Detection

Computer Science > Cryptography and Security [Submitted on 19 May 2026] Devilray: A Systematic Adversarial Model Revealing Blind Spots in Fake Base Station Detection Taekkyung Oh, Duckwoo Kim, Hansung Bae, Beomseok Oh, CheolJun Park, Tyler Tucker, Nathaniel Bennett, Sangwook Bae, Byeongdo Hong, Patrick Traynor, Yongdae Kim Fake Base Station (FBS) detection has been a critical focus of cellular security research for over two decades. However, significant financial and regulatory barriers to accessing commercial FBS (C-FBS) devices have limited direct visibility into real-world operations, forcing detection systems to be designed and evaluated around self-built prototypes. In this paper, we present Devilray, a reconfigurable and reference-grade adversarial baseline designed to systematically explore the realistic adversarial space and identify adversarial blind spots in current detection -- regions of realistic adversarial behavior excluded by prevailing threat models. We establish an empirical ground truth through the first academic analysis of a C-FBS and extend these observations into specification-driven operational variants permitted by 3GPP standards. Devilray enables the systematic exploration of 2,592 feasible and realistic FBS instances, capturing a wide range of operational possibilities. Using Devilray, we evaluate seven representative accessible FBS detectors and uncover coverage gaps across all seven, revealing blind spots rooted in assumption-bound design and evaluation. Our work provides the first robust adversarial model grounded in real-world behavior and specification analysis, enabling the community to develop and evaluate future detection mechanisms in a rigorous manner. Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2605.19232 [cs.CR]   (or arXiv:2605.19232v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2605.19232 Focus to learn more Submission history From: Taekkyung Oh [view email] [v1] Tue, 19 May 2026 01:04:22 UTC (2,001 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-05 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?)