{"data":{"id":"e6c125eb-69b1-4edc-9bda-3bc0b5d063cb","title":"Taming Generative Synthetic Data for X-Ray Prohibited Item Detection","summary":"This paper addresses the challenge of training prohibited item detection models for X-ray security screening, which normally requires large amounts of manually collected and labeled images. The authors propose Xsyn, a one-stage synthetic image generation pipeline using text-to-image generation (a type of AI that creates images from text descriptions) that automatically creates realistic X-ray security images without requiring labor-intensive manual image extraction and annotation.","solution":"N/A -- no mitigation discussed in source.","labels":["research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11560968","publishedAt":"2026-06-12T13:17:03.000Z","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":"2026-06-12T13:17:03.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":null,"aiComponentTargeted":"training_data","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}