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#artificial intelligence #cybersecurity Preprint

Last Secure Code Benchmark: Is the Code You Vibe Secure?

Tian-Yi Wu Chao Ge Peng Chen Feng-Ji Zhang Yong-Xin Wu Yu-Chong Xie Jian Li Chao-Yuan Peng Kai-Kai Zhang Dong Huang Ming-Zhe Du Yu-Kai Huang Jia-Heng Zhang Terry Yue Zhuo See-Kiong Ng
Oct 2026 · 0 citations · 36 references
Computer Science

Abstract

AI coding agents now write much of the code that ships, yet whether that code is secure remains unclear. We introduce the Last Secure Code Benchmark, a comprehensive evaluation of secure code generation by coding agents. Built from 150 real vulnerabilities, its 450 tasks span seven widely used languages (Java, C, C++, JavaScript, Python, PHP, and Go), 24 CWEs including 21 of the 2025 CWE Top 25 and 8 of the Top 10 KEV weaknesses, more than any benchmark we compare with, and three vibe-coding scenarios: filling in a function, writing a file, and building a repository's source tree from scratch. Every task asks only for functionality, through a specification that never mentions security, and hidden functional and security tests grade the result. Across six frontier agents, 73.6% to 91.3% of tasks pass functionally, yet even the strongest, Claude Fable 5, produces code that is both functional and secure for only 25.1% of tasks, and the others for 16.4% to 24.7%. The best model only passes 12% of the vulnerability scenarios across all vibe coding setting, posing strong concern on the security of the code written by vibe coding.

DOI arXiv Semantic Scholar
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