LATIDIA · Ciberseguridad

Detección autónoma de amenazas de OSS a través de LLM alineados con la taxonomía

arXiv: 2610.01263v1Announce Type: new Abstract: Los ecosistemas de software de código abierto (OSS) se enfrentan a crecientes amenazas de sofisticados ataques a la cadena de suministro, incluyendo typosquatting, confusión de dependencias, ofuscación de fuentes troyanas,

La noticia

arXiv:2610.01263v1 Announce Type: new Abstract: Open source software (OSS) ecosystems face growing threats from sophisticated supply chain attacks including typosquatting, dependency confusion, Trojan Source obfuscation, malicious build injection, and CI/CD pipeline poisoning. Existing detection approaches rely on signature-based tools and rule-based systems that struggle to generalize across attack variants and emerging threat patterns. In this paper we propose a taxonomy-aligned large language model framework for automated detection and classification of OSS supply chain threats. We introduce a structured AV-xxx threat taxonomy covering five attack categories and construct a curated dataset of 999 verified real-world OSS supply chain incidents sourced from GitHub Security Advisories, CISA alerts, and security research reports spanning