Author

Shae McFadden

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#artificial intelligence Review Dec 2024

Direction for Detection: A Survey of Automated Vulnerability Detection and all of its Pain Points

Security vulnerabilities in software can have severe consequences; however, manual vulnerability detection is costly and does not scale, especially as agentic coding frameworks increase the rate of code production. Over the last decade, a large body of research has applied machine learning machine learning to automate...

Dan Ristea, Shae McFadden, Ezzeldin Shereen et al. · 1 citation

#machine learning Preprint Aug 2026

REPLICANT: Learning Policies for Evading and Hardening Malware Detectors

This work presents Replicant, a deep reinforcement learning framework that learns the realistic task of evasion under a strict label-only black-box threat model and demonstrates that learning the task of evasion not only results in stronger attack performance but provides a better signal for hardening malware detectors...

Shae McFadden, Ilias Tsingenopoulos, Mario D'Onghia et al. · 0 citations