{"data":{"id":"d985aadb-7a9e-47b3-baa7-7dc3e3e06d4f","title":"Clara: A Cross-Modal Learning Framework for Enhanced Vulnerability Detection","summary":"Clara is a new framework for detecting software vulnerabilities (weaknesses in code that attackers can exploit) by combining information from multiple sources: code written as text sequences and code represented as graphs (visual structures showing how different parts connect). The framework uses two techniques to better blend this information together: a local fusion module that uses learnable prompts (instructions that guide the AI to focus on relevant details) to help different data types interact, and a global fusion module that uses attention mechanisms (ways of deciding what information matters most) to adaptively weigh contributions from each data source.","solution":"N/A -- no mitigation discussed in source.","labels":["research","security"],"sourceUrl":"http://ieeexplore.ieee.org/document/11514030","publishedAt":"2026-05-12T13:17:04.000Z","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":"2026-05-12T13:17:04.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.92,"researchCategory":"peer_reviewed","atlasIds":null}}