{"data":{"id":"3bc69e54-0321-4890-8523-87b2677669fb","title":"PPOM-Attack: A Substitute Model-Free Perturbation Prediction and Optimization Method for Black-Box Adversarial Attack Against Face Recognition","summary":"PPOM-Attack is a black-box attack against face recognition that avoids substitute models by taking feedback directly from the target model. It uses a proximal policy optimization (PPO)-based agent to predict and disturb perturbation regions in a face image, and a minimum brightness offsets method to keep adversarial images high quality. The authors report a 21.7% average gain in attack success rate over state-of-the-art FR attacks across seven FR models.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11406187","publishedAt":"2026-02-23T13:19:07.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"low","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":"2026-02-23T13:19:07.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["integrity","confidentiality"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.93,"researchCategory":"peer_reviewed","atlasIds":null}}