AuraForge: Scaling Security Supervision for Training Coding Agents
Coding agents are now proficient enough to generate complex software applications from a single prompt. As their capabilities have grown, human oversight has increasingly shifted from line-by-line code review toward hands-off evaluation of outcomes. However, recent studies have shown that such a transition exposes a critical risk: functional correctness alone does not guarantee a secure implementation. Despite growing attention to code security, training safer coding agents remains challenging because reliable security supervision is difficult to obtain at scale from real-world repositories. We introduce AuraForge to synthesize and validate executable security tests for training secure co...
| Authors | Danqing Wang, Songwen Zhao, Harsh Sharma et al. |
|---|---|
| Primary category | cs.CR |
| Published | 1 October 2026 |
| Last updated at source | 1 October 2026 |
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