Autonomous OSS Threat Detection via Taxonomy-Aligned LLMs
The research developed a framework using GPT-4 and taxonomy-aligned prompts to automatically detect and classify open source software (OSS) supply chain threats. This method achieved 97.0% accuracy across five threat categories, significantly outperforming traditional machine learning models. The key finding is that structured prompting based on explicit threat definitions is more effective than simply increasing model size or fine-tuning.