{"data":{"id":"437be396-1a6d-4b37-ae62-2f3d77e57557","title":"Frequency Bias Matters: Diving Into Robust and Generalized Deep Image Forgery Detection","summary":"Researchers study why deep image forgery detectors fail to generalize to unseen GANs and to noisy samples. They trace both problems to a frequency bias in DNN detectors and propose a two-step frequency alignment method that removes the frequency discrepancy between real and fake images. The method works as a black-box attack on detectors or as a universal defense, tested across twelve detectors, eight forgery models and five metrics.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11271606","publishedAt":"2025-12-01T13:16:17.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["model_evasion"],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":["GAN-based image generators"],"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":"2025-12-01T13:16:17.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["integrity"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.93,"researchCategory":"peer_reviewed","atlasIds":null}}