{"data":{"id":"4073c998-c807-427f-a08d-dede04deeb0a","title":"EXE-Bench: Ranking the Tradeoffs of AI-Based Windows Malware Detectors for Real-World Usability","summary":"Existing evaluations of AI-based Windows malware detectors differ in training and test data, lack temporal analysis, skip adversarial content-injection tests, and ignore deployment compute costs, so they cannot show which detector to deploy. The authors introduce EXE-Bench, which assesses performance, temporal and adversarial robustness, and computational overhead, combining them into one score for direct comparison. Their analysis finds that feature-engineered domain knowledge remains highly useful, resisting both time and adversarial attacks, while most deep networks excel only right after deployment.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11695264","publishedAt":"2026-09-17T13:32:35.000Z","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":"2026-09-17T13:32:35.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":null,"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}