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Athena system uses knowledge graphs to identify vulnerable software libraries

By PulseAugur Editorial · [1 sources] ·

Researchers have developed Athena, a novel graph-based system designed to identify libraries affected by software vulnerabilities. Unlike previous methods that treat vulnerability data as isolated text, Athena models this information as a knowledge graph. The system uses knowledge graph completion techniques to predict missing affected library details for given vulnerabilities. A final re-ranking module further refines these predictions by combining graph embeddings with LLM analysis, achieving a significant improvement over existing state-of-the-art approaches. AI

IMPACT This research could improve the accuracy of vulnerability databases, leading to more secure software development practices.

RANK_REASON The cluster describes a research paper detailing a new system and methodology for a specific technical problem. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Athena system uses knowledge graphs to identify vulnerable software libraries

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The cluster describes a research paper detailing a new system and methodology for a specific technical problem. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Phong Trinh Duy, Trang Dang Yen, Hung Nguyen-Huu, Bach Le, Quyet-Thang Huynh, Dieu Hoang Vu, David Lo, Thanh Le-Cong ·

    Athena: Vulnerability-Affected Library Identification via Knowledge Graph Completion

    arXiv:2609.01187v1 Announce Type: cross Abstract: A single vulnerability in a widely used library can cascade through millions of dependent applications, yet more than half of vulnerability database entries contain missing or incorrect affected-library information. Existing autom…

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