{"data":{"id":"10d183b4-0d0d-44ce-83d9-5e23d5f84a9e","title":"Feature-Alteration Robustness for Out-of-Distribution Detection","summary":"The paper proposes Feature-alteration Robustness (FAR), a method for out-of-distribution (OOD) detection. It rests on the observation that a pretrained in-distribution model stays robust when its intermediate feature maps are altered, while OOD features are heavily distorted. FAR alters intermediate feature maps and measures foreground-background deviations after several layers, and the authors report state-of-the-art results on various benchmarks, alone and combined with ASH.","solution":"N/A -- no mitigation discussed in source.","labels":["research","security"],"sourceUrl":"http://ieeexplore.ieee.org/document/11655504","publishedAt":"2026-08-13T13:16:47.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedPackageNames":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":"2026-08-13T13:16:47.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":null,"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.8,"researchCategory":"peer_reviewed","atlasIds":null}}