A Large-scale Study of Security Vulnerability Support on Developer Q&A Websites
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Abstract (arXiv)
Context: Security Vulnerabilities (SVs) pose many serious threats to software systems. Developers usually seek solutions to addressing these SVs on developer Question and Answer (Q&A) websites. However, there is still little known about on-going SV-specific discussions on different developer Q&A sites. Objective: We present a large-scale empirical study to understand developers' SV discussions and how these discussions are being supported by Q&A sites. Method: We first curate 71,329 SV posts from two large Q&A sites, namely Stack Overflow (SO) and Security StackExchange (SSE). We then use topic modeling to uncover the topics of SV-related discussions and analyze the popularity, difficulty, and level of expertise for each topic. We also perform a qualitative analysis to identify the types of solutions to SV-related questions. Results: We identify 13 main SV discussion topics on Q&A sites. Many topics do not follow the distributions and trends in expert-based security sources such as Common Weakness Enumeration (CWE) and Open Web Application Security Project (OWASP). We also discover that SV discussions attract more experts to answer than many other domains, but some difficult SV topics (e.g., Vulnerability Scanning Tools) still receive quite limited support from experts. Moreover, we identify seven key types of answers given to SV questions on Q&A sites, in which SO often provides code and instructions, while SSE usually gives experience-based advice and explanations. Conclusion: Our findings provide support for researchers and practitioners to effectively acquire, share and leverage SV knowledge on Q&A sites.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Aug 2020.
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Citing papers per year: 2021: 3; 2022: 1; 2023: 0; 2024: 6; 2025: 1; 2026: 1.
12 papers.
- 2021A Survey on Data-driven Software Vulnerability Assessment and Prioritizationcited by 18
- 2021DeepCVA: Automated Commit-level Vulnerability Assessment with Deep Multi-task Learningcited by 11
- 2024Are Latent Vulnerabilities Hidden Gems for Software Vulnerability Prediction? An Empirical Studycited by 9
- 2025LLMSecConfig: An LLM-Based Approach for Fixing Software Container Misconfigurationscited by 9
- 2024Software Vulnerability Prediction in Low-Resource Languages: An Empirical Study of CodeBERT and ChatGPTcited by 8
- 2021Automated Security Assessment for the Internet of Thingscited by 6
- 2024Mitigating Data Imbalance for Software Vulnerability Assessment: Does Data Augmentation Help?cited by 6
- 2024Automated Code-centric Software Vulnerability Assessment: How Far Are We? An Empirical Study in C/C++cited by 6
- 2024Automatic Data Labeling for Software Vulnerability Prediction Models: How Far Are We?cited by 6
- 2022On the Use of Fine-grained Vulnerable Code Statements for Software Vulnerability Assessment Modelscited by 5
- 2024PatUntrack: Automated Generating Patch Examples for Issue Reports without Tracked Insecure Codecited by 1
- 2026Inference-Time Safety For Code LLMs Via Retrieval-Augmented Revisioncited by 0
- 2026Inference-Time Safety For Code LLMs Via Retrieval-Augmented Revision2 Mar 2026
- 2025LLMSecConfig: An LLM-Based Approach for Fixing Software Container Misconfigurations4 Feb 2025
- 2024PatUntrack: Automated Generating Patch Examples for Issue Reports without Tracked Insecure Code16 Aug 2024
- 2024Automatic Data Labeling for Software Vulnerability Prediction Models: How Far Are We?25 Jul 2024
- 2024Automated Code-centric Software Vulnerability Assessment: How Far Are We? An Empirical Study in C/C++24 Jul 2024
- 2024Mitigating Data Imbalance for Software Vulnerability Assessment: Does Data Augmentation Help?15 Jul 2024
- 2024Software Vulnerability Prediction in Low-Resource Languages: An Empirical Study of CodeBERT and ChatGPT26 Apr 2024
- 2024Are Latent Vulnerabilities Hidden Gems for Software Vulnerability Prediction? An Empirical Study20 Jan 2024
- 2022On the Use of Fine-grained Vulnerable Code Statements for Software Vulnerability Assessment Models16 Mar 2022
- 2021Automated Security Assessment for the Internet of Things9 Sep 2021
- 2021DeepCVA: Automated Commit-level Vulnerability Assessment with Deep Multi-task Learning18 Aug 2021
- 2021A Survey on Data-driven Software Vulnerability Assessment and Prioritization18 Jul 2021