{"data":{"id":"4920a55d-be09-4716-903f-887f14c1ba06","title":"MaliVD: Source Code Vulnerability Localization via Attention-Based Multi-Modal Learning","summary":"MaliVD is a deep learning method that detects vulnerabilities (security flaws) in source code and identifies exactly which lines contain them, using a multi-modal attention mechanism (a technique that lets the AI focus on important parts of code by analyzing it in multiple ways, like looking at the code's sequence, tree structure, and relationships between components). Traditional security tools create too many false alarms and struggle with complex modern software, but MaliVD performs better than eight other detection methods by extracting different types of code features and prioritizing suspicious sections.","solution":"N/A -- no mitigation discussed in source.","labels":["research","security"],"sourceUrl":"http://ieeexplore.ieee.org/document/11475050","publishedAt":"2026-04-06T13:20:24.000Z","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":"2026-04-06T13:20:24.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity"],"aiComponentTargeted":"framework","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}