ABLE uses LLMs with sanitization and iterative refinement to generate bypass YARA rules from malware traces, achieving 79% success on 334 samples and 47% more family detections.
A reverse engineering education needs analysis survey.arXiv preprint arXiv:2212.07531, 2022
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A Large Language Model Approach to Generating Bypass Rules for Malware Evasion in Analysis Sandbox
ABLE uses LLMs with sanitization and iterative refinement to generate bypass YARA rules from malware traces, achieving 79% success on 334 samples and 47% more family detections.