A Queryable Graph-Based Security Analysis Framework for O-RAN

• URL: http://arxiv.org/abs/2609.06855v1
• Date: Sun, 06 Sep 2026 22:01:04 GMT
• Title: A Queryable Graph-Based Security Analysis Framework for O-RAN
• Abstract summary: The Open Radio Access Network (O-RAN) replaces vendor-locked RANs with a modular and interoperable architecture that fosters competition and accelerates innovation.<n>Today, assessing O-RAN security requires manually cross-referencing dozens of specifications, vendor whitepapers, and academic studies, which is error-prone and static.<n>We present a graph-based framework that transforms this static corpus into a single, queryable database.
• Score: 5.968342460171346
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The Open Radio Access Network (O-RAN) replaces vendor-locked RANs with a modular and interoperable architecture that fosters competition and accelerates innovation. With this openness comes increased complexity and a larger attack surface, making security a critical concern. Today, assessing O-RAN security requires manually cross-referencing dozens of specifications, vendor whitepapers, and academic studies, which is error-prone and static. In this paper, we present a graph-based framework that transforms this static corpus into a single, queryable database. Our graph representation contains over 350 nodes and more than 1,250 relationships, distilled from specifications, academic papers, open-source projects, and vulnerability databases. To keep this resource current, we integrate a hybrid data extraction pipeline that couples deterministic parsing of structured specifications with Large Language Model (LLM)-assisted extraction for evolving specifications and unstructured literature. Querying the graph reveals three actionable findings within our curated corpus: critical infrastructure such as the O-DU, SMO, and O-Cloud carries dozens of specification-level threats yet has little or no empirical coverage; memory-safety weaknesses account for 11 of the 21 CWE occurrences associated with the analyzed CVEs; and fuzzing uncovered 18 of the 20 CVEs attributed to research papers. We provide the database, pipeline, and queries as open-source artifacts.

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