{"data":{"id":"da06526f-70ea-48f5-aec8-1852b82a4c9c","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","summary":"DiffMI is a diffusion-driven, training-free model inversion attack that recovers identity information from face recognition systems that map facial images to embeddings. The method combines latent code initialization, ranked adversarial refinement, and a confidence-aware optimization objective, and it applies directly to unseen target identities. The authors report 84.42%–92.87% attack success rates against inversion-resilient systems, 4.01%–9.82% higher than the best prior training-free GAN-based approach. The implementation is available at https://github.com/azrealwang/DiffMI.","solution":"N/A -- no mitigation discussed in source.","labels":["security","privacy","research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11482232","publishedAt":"2026-04-16T13:17:03.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"low","attackType":[],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":["face recognition models"],"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":"2026-04-16T13:17:03.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["confidentiality"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.93,"researchCategory":"peer_reviewed","atlasIds":null}}