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[2602.15485] SecCodeBench-V2 Technical Report
Summary
SecCodeBench-V2 is a benchmark for evaluating LLMs' ability to generate secure code, featuring 98 scenarios across five programming languages and a robust evaluation pipeline.
Why It Matters
As AI coding assistants become integral to software development, ensuring their ability to produce secure code is crucial. SecCodeBench-V2 offers a standardized method to assess these models, addressing security vulnerabilities in generated code, which is vital for maintaining software integrity and safety.
Key Takeaways
- SecCodeBench-V2 includes 98 scenarios for evaluating secure code generation.
- The benchmark covers five programming languages: Java, C, Python, Go, and others.
- A unified evaluation pipeline uses dynamic execution to validate model outputs.
- Test cases are authored by security experts to ensure high fidelity and reliability.
- The benchmark aims to improve the security posture of AI coding assistants.
Computer Science > Cryptography and Security arXiv:2602.15485 (cs) [Submitted on 17 Feb 2026] Title:SecCodeBench-V2 Technical Report Authors:Longfei Chen, Ji Zhao, Lanxiao Cui, Tong Su, Xingbo Pan, Ziyang Li, Yongxing Wu, Qijiang Cao, Qiyao Cai, Jing Zhang, Yuandong Ni, Junyao He, Zeyu Zhang, Chao Ge, Xuhuai Lu, Zeyu Gao, Yuxin Cui, Weisen Chen, Yuxuan Peng, Shengping Wang, Qi Li, Yukai Huang, Yukun Liu, Tuo Zhou, Terry Yue Zhuo, Junyang Lin, Chao Zhang View a PDF of the paper titled SecCodeBench-V2 Technical Report, by Longfei Chen and 26 other authors View PDF HTML (experimental) Abstract:We introduce SecCodeBench-V2, a publicly released benchmark for evaluating Large Language Model (LLM) copilots' capabilities of generating secure code. SecCodeBench-V2 comprises 98 generation and fix scenarios derived from Alibaba Group's industrial productions, where the underlying security issues span 22 common CWE (Common Weakness Enumeration) categories across five programming languages: Java, C, Python, Go, and this http URL. SecCodeBench-V2 adopts a function-level task formulation: each scenario provides a complete project scaffold and requires the model to implement or patch a designated target function under fixed interfaces and dependencies. For each scenario, SecCodeBench-V2 provides executable proof-of-concept (PoC) test cases for both functional validation and security verification. All test cases are authored and double-reviewed by security experts, ensuring high fidelity, ...
