{"data":{"id":"1d2e2ef3-e530-4e30-aa11-aa4884cc648c","title":"Byzantine-Robust Muon: Resilient Momentum Orthogonalization for Distributed Learning","summary":"This paper analyzes Byzantine-robust distributed and federated learning with the Muon optimizer, using a unified first-order trust-region framework and robust aggregation, without assuming i.i.d. data. It establishes convergence guarantees for non-convex and star-convex objectives, with an additive heterogeneity error floor. In simulated federated experiments on CIFAR-10, TinyStories and other benchmarks, the tested Muon configurations achieved higher attacked accuracy or lower perplexity than the tested baselines.","solution":"N/A -- no mitigation discussed in source.","labels":["research","security"],"sourceUrl":"https://arxiv.org/abs/2611.13137v1","publishedAt":"2026-11-09T19:18:37.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["other"],"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":"2026-11-09T19:18:37.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["integrity"],"aiComponentTargeted":"framework","llmSpecific":false,"classifierConfidence":0.92,"researchCategory":"preprint","atlasIds":null}}