{"data":{"id":"4f6eb63f-8ba4-408a-bcc8-e491b1f9909a","title":"Mujaz: A Summarization-Based Approach for Normalized Vulnerability Description","summary":"Mujaz is a system that uses natural language processing (NLP, the field of AI that helps computers understand human language) to automatically clean up and summarize vulnerability descriptions found in public databases. The system was trained on a collection of carefully labeled vulnerability summaries and uses pre-trained language models (AI systems trained on large amounts of text) to create clearer, more consistent descriptions that help developers and organizations understand and patch security issues more effectively.","solution":"N/A -- no mitigation discussed in source.","labels":["research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11198914","publishedAt":"2025-10-09T13:17:21.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"patchAvailable":null,"disclosureDate":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":null,"aiComponentTargeted":"framework","llmSpecific":false,"classifierConfidence":0.75,"researchCategory":"peer_reviewed","atlasIds":null}}