Author

Dmitrijs Trizna

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Jul 2026

HoF-Bench: Rediscovering Real AI-Discovered CVEs Without Frontier Models

HoF-Bench (named after AISLE's public Hall of Fame), a benchmark built from 95 public AI-discovered CVEs across eight repositories pinned at vulnerable commits, provides a compact test bed for comparing vulnerability scanners, their reliability across repeated runs, and the candidate volume they create.

P. Simecek, Elnaz Babayeva, Jiří Balhar et al. · arXiv.org · 0 citations

Jul 2026

EXE-Bench: Ranking the Tradeoffs of AI-based Windows Malware Detectors for Real-World Usability

ExE-Bench assesses performance, temporal and adversarial robustness, and computational overhead, aggregating them into a single score for direct and fair model comparison, and highlights how evaluations conducted only after deployment are suboptimal and unable to provide a complete picture of their performance.

Andrea Ponte, Daniel Gibert, M. Kozák et al. · arXiv.org · 0 citations