{"data":{"id":"e21fda5e-034d-49a9-a33b-40a9f7878990","title":"GraphRectify: Graph-Based Transfer of Adversarial Example Detectors Across Neural Networks","summary":"GraphRectify is a graph-based framework that transfers adversarial image detectors from one classifier backbone to another. It learns a structured representation of intermediate classifier features and adapts features from a new backbone to the detector trained on the original model. Across the evaluation matrix, it achieves higher aggregate ROC-AUC than training a detector from scratch on the new backbone, with the largest gains between different backbone families when sufficient data are available.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"https://arxiv.org/abs/2610.10423v1","publishedAt":"2026-10-07T17:03:55.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["model_evasion"],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-5-5","classifierPromptVersion":"v4","summaryPromptVersion":"v2","headline":null,"headlinePromptVersion":null,"cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"epssCheckedAt":null,"kevDateAdded":null,"advisoryAliases":null,"affectedPackagesSource":null,"affectedPackagesCheckedAt":null,"patchAvailable":null,"disclosureDate":"2026-10-07T17:03:55.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["integrity"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.93,"researchCategory":"preprint","atlasIds":null}}