Identifying Smart Contract Security Issues in Code Snippets from Stack Overflow
Jiachi Chen, Chong Chen, Jiang Hu, John C. Grundy, Yanlin Wang, Ting Chen, Zibin Zheng
摘要
Smart contract developers frequently seek solutions to developmental challenges on Q&A platforms such as Stack Overflow (SO). Although community responses often provide viable solutions, the embedded code snippets can also contain hidden vulnerabilities. Integrating such code directly into smart contracts may make them susceptible to malicious attacks. We conducted an online survey and received 74 responses from smart contract developers. The results of this survey indicate that the majority (86.4%) of participants do not sufficiently consider security when reusing SO code snippets. Despite the existence of various tools designed to detect vulnerabilities in smart contracts, these tools are typically developed for analyzing fully-completed smart contracts and thus are ineffective for analyzing typical code snippets as found on SO. We introduce SOChecker, the first tool designed to identify potential vulnerabilities in incomplete SO smart contract code snippets. SOChecker first leverages a fine-tuned Llama2 model for code completion, followed by the application of symbolic execution methods for vulnerability detection. Our experimental results, derived from a dataset comprising 897 code snippets collected from smart contract-related SO posts, demonstrate that SOChecker achieves an F1 score of 68.2%, greatly surpassing GPT-3.5 and GPT-4 (20.9% and 33.2% F1 Scores respectively). Our findings underscore the need to improve the security of code snippets from Q&A websites.
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引用它的顶会 Paper8
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- RMCBench: Benchmarking Large Language Models' Resistance to Malicious CodeJiachi Chen, Qingyuan Zhong, Yanlin Wang, Kaiwen Ning 等ASE 2024 · 被引用 6 次
- SmartCoder-R1: Towards Secure and Explainable Smart Contract Generation with Security-Aware Group Relative Policy OptimizationLei Yu, Jingyuan Zhang, Xin Wang, Li Yang 等FSE 2026 · 被引用 3 次
- DrainCode: Stealthy Energy Consumption Attacks on Retrieval-Augmented Code Generation via Context PoisoningYanli Wang, Jiadong Wu, Tianyue Jiang, Mingwei Liu 等ASE 2025 · 被引用 3 次
- AlignCoder: Aligning Retrieval with Target Intent for Repository-Level Code CompletionTianyue Jiang, Yanlin Wang, Yanli Wang, Daya Guo 等ASE 2025 · 被引用 2 次
它引用的顶会 Paper17
- LoRA: Low-Rank Adaptation of Large Language ModelsEdward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu 等ICLR 2022 · 被引用 18,833 次
- Making Smart Contracts SmarterLoi Luu, Duc-Hiep Chu, Hrishi Olickel, Prateek Saxena 等CCS 2016 · 被引用 2,306 次
- Securify: Practical Security Analysis of Smart ContractsPetar Tsankov, Andrei Marian Dan, Dana Drachsler-Cohen, Arthur Gervais 等CCS 2018 · 被引用 1,108 次
- EAGLE: Speculative Sampling Requires Rethinking Feature UncertaintyYuhui Li, Fangyun Wei, Chao Zhang, Hongyang ZhangICML 2024 · 被引用 424 次
- Empirical review of automated analysis tools on 47, 587 Ethereum smart contractsThomas Durieux, João F. Ferreira, Rui Abreu, Pedro CruzICSE 2020 · 被引用 373 次
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