Is Your AI-Generated Code Really Safe? Evaluating Large Language Models on Secure Code Generation with CodeSecEval
Fuente:
arXiv
Saved in:
| Main Authors: | Wang, Jiexin, Luo, Xitong, Cao, Liuwen, He, Hongkui, Huang, Hailin, Xie, Jiayuan, Jatowt, Adam, Cai, Yi |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
SecCodePRM: A Process Reward Model for Code Security
by: Yu, Weichen, et al.
Published: (2026)
by: Yu, Weichen, et al.
Published: (2026)
RealSec-bench: A Benchmark for Evaluating Secure Code Generation in Real-World Repositories
by: Wang, Yanlin, et al.
Published: (2026)
by: Wang, Yanlin, et al.
Published: (2026)
Does Teaming-Up LLMs Improve Secure Code Generation? A Comprehensive Evaluation with Multi-LLMSecCodeEval
by: Sabir, Bushra, et al.
Published: (2026)
by: Sabir, Bushra, et al.
Published: (2026)
Codexity: Secure AI-assisted Code Generation
by: Kim, Sung Yong, et al.
Published: (2024)
by: Kim, Sung Yong, et al.
Published: (2024)
ArkEval: Benchmarking and Evaluating Automated CodeRepair for ArkTS
by: Xie, Bang, et al.
Published: (2026)
by: Xie, Bang, et al.
Published: (2026)
ComplexCodeEval: A Benchmark for Evaluating Large Code Models on More Complex Code
by: Feng, Jia, et al.
Published: (2024)
by: Feng, Jia, et al.
Published: (2024)
PromSec: Prompt Optimization for Secure Generation of Functional Source Code with Large Language Models (LLMs)
by: Nazzal, Mahmoud, et al.
Published: (2024)
by: Nazzal, Mahmoud, et al.
Published: (2024)
ProSec: Fortifying Code LLMs with Proactive Security Alignment
by: Xu, Xiangzhe, et al.
Published: (2024)
by: Xu, Xiangzhe, et al.
Published: (2024)
CodeScore: Evaluating Code Generation by Learning Code Execution
by: Dong, Yihong, et al.
Published: (2023)
by: Dong, Yihong, et al.
Published: (2023)
SR-Eval: Evaluating LLMs on Code Generation under Stepwise Requirement Refinement
by: Zhan, Zexun, et al.
Published: (2025)
by: Zhan, Zexun, et al.
Published: (2025)
Rethinking the Evaluation of Secure Code Generation
by: Dai, Shih-Chieh, et al.
Published: (2025)
by: Dai, Shih-Chieh, et al.
Published: (2025)
Do AI Agents Really Improve Code Readability?
by: Horikawa, Kyogo, et al.
Published: (2026)
by: Horikawa, Kyogo, et al.
Published: (2026)
Is Vibe Coding Safe? Benchmarking Vulnerability of Agent-Generated Code in Real-World Tasks
by: Zhao, Songwen, et al.
Published: (2025)
by: Zhao, Songwen, et al.
Published: (2025)
ScenEval: A Benchmark for Scenario-Based Evaluation of Code Generation
by: Paul, Debalina Ghosh, et al.
Published: (2024)
by: Paul, Debalina Ghosh, et al.
Published: (2024)
CoderEval: A Benchmark of Pragmatic Code Generation with Generative Pre-trained Models
by: Yu, Hao, et al.
Published: (2023)
by: Yu, Hao, et al.
Published: (2023)
DevEval: Evaluating Code Generation in Practical Software Projects
by: Li, Jia, et al.
Published: (2024)
by: Li, Jia, et al.
Published: (2024)
SolContractEval: A Benchmark for Evaluating Contract-Level Solidity Code Generation
by: Ye, Zhifan, et al.
Published: (2025)
by: Ye, Zhifan, et al.
Published: (2025)
RedCode: Risky Code Execution and Generation Benchmark for Code Agents
by: Guo, Chengquan, et al.
Published: (2024)
by: Guo, Chengquan, et al.
Published: (2024)
AI Code Generators for Security: Friend or Foe?
by: Natella, Roberto, et al.
Published: (2024)
by: Natella, Roberto, et al.
Published: (2024)
AI Code in the Wild: Measuring Security Risks and Ecosystem Shifts of AI-Generated Code in Modern Software
by: Wang, Bin, et al.
Published: (2025)
by: Wang, Bin, et al.
Published: (2025)
LiCoEval: Evaluating LLMs on License Compliance in Code Generation
by: Xu, Weiwei, et al.
Published: (2024)
by: Xu, Weiwei, et al.
Published: (2024)
Evaluation of Code LLMs on Geospatial Code Generation
by: Gramacki, Piotr, et al.
Published: (2024)
by: Gramacki, Piotr, et al.
Published: (2024)
On Evaluating the Efficiency of Source Code Generated by LLMs
by: Niu, Changan, et al.
Published: (2024)
by: Niu, Changan, et al.
Published: (2024)
SolEval: Benchmarking Large Language Models for Repository-level Solidity Code Generation
by: Peng, Zhiyuan, et al.
Published: (2025)
by: Peng, Zhiyuan, et al.
Published: (2025)
Fortifying LLM-Based Code Generation with Graph-Based Reasoning on Secure Coding Practices
by: Patir, Rupam, et al.
Published: (2025)
by: Patir, Rupam, et al.
Published: (2025)
SecCodeBench-V2 Technical Report
by: Chen, Longfei, et al.
Published: (2026)
by: Chen, Longfei, et al.
Published: (2026)
CFCEval: Evaluating Security Aspects in Code Generated by Large Language Models
by: Cheng, Cheng, et al.
Published: (2025)
by: Cheng, Cheng, et al.
Published: (2025)
DevEval: A Manually-Annotated Code Generation Benchmark Aligned with Real-World Code Repositories
by: Li, Jia, et al.
Published: (2024)
by: Li, Jia, et al.
Published: (2024)
SALLM: Security Assessment of Generated Code
by: Siddiq, Mohammed Latif, et al.
Published: (2023)
by: Siddiq, Mohammed Latif, et al.
Published: (2023)
A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code
by: Lian, Keke, et al.
Published: (2025)
by: Lian, Keke, et al.
Published: (2025)
An Empirical Security Evaluation of LLM-Generated Cryptographic Rust Code
by: Elsayed, Mohamed, et al.
Published: (2026)
by: Elsayed, Mohamed, et al.
Published: (2026)
CodeArena: A Collective Evaluation Platform for LLM Code Generation
by: Du, Mingzhe, et al.
Published: (2025)
by: Du, Mingzhe, et al.
Published: (2025)
Contextualized Code Pretraining for Code Generation
by: Liu, Chen, et al.
Published: (2026)
by: Liu, Chen, et al.
Published: (2026)
UniCode: Augmenting Evaluation for Code Reasoning
by: Zheng, Xinyue, et al.
Published: (2025)
by: Zheng, Xinyue, et al.
Published: (2025)
ClassEval-Pro: A Cross-Domain Benchmark for Class-Level Code Generation
by: Chen, Yeheng, et al.
Published: (2026)
by: Chen, Yeheng, et al.
Published: (2026)
CodeJudge-Eval: Can Large Language Models be Good Judges in Code Understanding?
by: Zhao, Yuwei, et al.
Published: (2024)
by: Zhao, Yuwei, et al.
Published: (2024)
ClarEval: A Benchmark for Evaluating Clarification Skills of Code Agents under Ambiguous Instructions
by: Li, Jialin, et al.
Published: (2026)
by: Li, Jialin, et al.
Published: (2026)
ProjectEval: A Benchmark for Programming Agents Automated Evaluation on Project-Level Code Generation
by: Liu, Kaiyuan, et al.
Published: (2025)
by: Liu, Kaiyuan, et al.
Published: (2025)
Assessing the Quality and Security of AI-Generated Code: A Quantitative Analysis
by: Sabra, Abbas, et al.
Published: (2025)
by: Sabra, Abbas, et al.
Published: (2025)
Code Fingerprints: Disentangled Attribution of LLM-Generated Code
by: Guo, Jiaxun, et al.
Published: (2026)
by: Guo, Jiaxun, et al.
Published: (2026)
Similar Items
-
SecCodePRM: A Process Reward Model for Code Security
by: Yu, Weichen, et al.
Published: (2026) -
RealSec-bench: A Benchmark for Evaluating Secure Code Generation in Real-World Repositories
by: Wang, Yanlin, et al.
Published: (2026) -
Does Teaming-Up LLMs Improve Secure Code Generation? A Comprehensive Evaluation with Multi-LLMSecCodeEval
by: Sabir, Bushra, et al.
Published: (2026) -
Codexity: Secure AI-assisted Code Generation
by: Kim, Sung Yong, et al.
Published: (2024) -
ArkEval: Benchmarking and Evaluating Automated CodeRepair for ArkTS
by: Xie, Bang, et al.
Published: (2026)