Synthetic Training of Code Llama for Zero-Shot CVE Detection Accuracy

This report synthesises findings from 3 peer-reviewed papers addressing the following research question: How does training Code Llama on synthetic vulnerability datasets impact its zero-shot detection accuracy on real-world CVE benchmarks compared to fine-tuning on Big-Vul. 8 claims were extracted from source literature; 8 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 8.3/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research goal: How does training Code Llama on synthetic vulnerability datasets impact its zero-shot detection accuracy on real-world CVE benchmarks compared to fine-tuning on Big-Vul?

Autonomous literature synthesis. Automated review score: 8.3/10. Full text and citation available at Assignee Research.