arXiv Computation and Language By Danqing Wang, Baolin Peng, Zhepei Wei, Isadora White, Wenlin Yao, Hao Cheng, Qianhui Wu, Minseon Kim, Xingdi Yuan, Lei Li, Jianfeng Gao

SecureVibe: Making Vibe Coding More Secure

Read the original on arXiv Computation and Language →

SecureVibe is a training recipe designed to enhance the security of vibe coding by explicitly targeting planning and testing for code security. It combines supervised fine‑tuning on a security suite with post‑training methods (SECUREVIBE_rl and SECUREVIBE_hg) that use verifiable execution feedback and hint‑based self‑supervision. The approach outperforms baselines on multiple security coding benchmarks, improving security pass@1 by up to 6.9 points on BaxBench and 11.5 points on SusVibes, while also boosting functionality pass@1 on both security and generic coding tasks.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

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