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cs.CR2026
Trident: Improving Malware Detection with LLMs and Behavioral Features
Rebecca Saul, Jingzhi Jiang, Elliott Chia +1
Traditionally, machine learning methods for PE malware detection have relied on static features like byte histograms, string information, and PE header contents. One barrier to inc…
cs.CR2025
SCGAgent: Recreating the Benefits of Reasoning Models for Secure Code Generation with Agentic Workflows
Rebecca Saul, Hao Wang, Koushik Sen +1
Large language models (LLMs) have seen widespread success in code generation tasks for different scenarios, both everyday and professional. However current LLMs, despite producing…
cs.CR2024
Assemblage: Automatic Binary Dataset Construction for Machine Learning
Chang Liu, Rebecca Saul, Yihao Sun +5
Binary code is pervasive, and binary analysis is a key task in reverse engineering, malware classification, and vulnerability discovery. Unfortunately, while there exist large corp…