{"data":{"id":"e9c2ab4e-c1a1-4263-a994-ead77f4d332f","title":"PrivMark: Pixel-Space Steering against Privacy Leakage in Vision-Language Models","summary":"PrivMark is a framework that suppresses soft-biometric leakage, such as age, gender, and race, from vision-language models by adding a bounded pixel-space perturbation to the image. It combines two steering vector directions in hidden-state space, one for incidental disclosure under open-ended descriptions and one for compliance with direct biometric probes. Across three white-box source models it reaches up to 85.9% biometric suppression while keeping 75% of clean OK-VQA utility, and the perturbations transfer to seven unseen VLMs, including closed-source APIs.","solution":"N/A -- no mitigation discussed in source.","labels":["privacy","research"],"sourceUrl":"https://arxiv.org/abs/2611.10528v1","publishedAt":"2026-11-07T06:58:41.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["pii_leakage"],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":["vision-language models","closed-source VLM APIs"],"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":"2026-11-07T06:58:41.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["confidentiality"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.95,"researchCategory":"preprint","atlasIds":null}}