Athena: Vulnerability-Affected Library Identification via Knowledge Graph Completion

Athena is a graph-based system that identifies affected libraries for software vulnerabilities by modeling vulnerability databases as a knowledge graph and applying knowledge graph completion. It integrates CVEs, libraries, CWE types, CPE products, and software ecosystems, then predicts missing affected libraries using link prediction and refines results with a fine‑tuned LLM that incorporates graph embeddings. Experiments on the VulLib dataset show Athena outperforms four state‑of‑the‑art baselines, achieving a 32% higher average F1 score and demonstrating that a smaller KGC backbone can surpass larger LLM‑only approaches.

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• llms
• rag
• fine-tuning
• benchmarks