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Detection and Explanation of PowerShell Malware with Large Language Models
The application of LLMs for detecting malicious PowerShell scripts and producing human-interpretable explanations for their classification decisions are investigated, showing that LLMs are capable of identifying and explaining malicious PowerShell scripts, although performance varies across different models.
LADE: LLM-Assisted Advanced Persistent Threat Detection and Explanation
Experimental results show that LLMs, when guided by rubric-based prompts and supplemented with ATT&CK domain knowledge, achieve robust performance across detection, localization, and TTP mapping tasks.