{"data":{"id":"3deab006-fde8-4b8b-b2f2-b010c5469f26","title":"Model-Aware Generation of Safety-Critical Scenes for Robust End-to-End Driving via Distilled Planner Surrogates","summary":"A failure-mode analysis on NeuroNCAP finds that 95.9% of DiffusionDrive's collisions are planning failures despite reliable detection, which the authors attribute to rare safety-critical interactions in real driving logs. They propose a model-aware framework that generates 50 safety-critical scenes per planner, each pairing an attack with a safe escape trajectory, via a BEV-level differentiable surrogate distilled from the planner's own planning head. Fine-tuning on these scenes roughly halves the closed-loop collision rate of SparseDrive (28.0% to 12.2%) and DiffusionDrive (37.5% to 19.2%), with gains concentrated on the planner each scene set was generated against.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"https://arxiv.org/abs/2610.35448v1","publishedAt":"2026-10-26T13:44:59.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["model_evasion"],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":["SparseDrive","DiffusionDrive","NeuroNCAP"],"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":"2026-10-26T13:44:59.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["safety","integrity"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.9,"researchCategory":"preprint","atlasIds":null}}