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P2 Leveraging Practitioners’ Feedback to Improve a Security Linter

利用从业者反馈改进安全 Linter
ASE Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering2022匹配度 4/10 · 该论文关注静态分析安全 linter 的误报改进与工业落地,并通过开发者反馈调整规则,与“静态分析工程/问题驱动”有一定交集;但它不涉及 LLM/Agent、ML 系统、浮点程序分析或贝叶斯程序分析,与用户核心的 PL 与 AI 交叉方向关联有限。引用 16 inbox
Sofia Reis, Rui Abreu, Marcelo d'Amorim, Daniel Fortunato
crossref: 2026-09-12

AI 速览

一句话:通过访谈专业开发者反馈,调整和扩展 Puppet 安全 linter 规则,显著提升 IaC 安全检测精确率。

IaC 允许以代码管理基础设施,但大量模板存在安全漏洞;现有 IaC 安全 linter 误报率高、可靠性不足。本文通过访谈专业开发者,收集他们对当前最先进 Puppet 安全 linter 不精确根因的反馈。基于反馈,作者调整了原有规则集中的 7 条规则并新增 3 条规则,开发出改进版 linter。随后对 131 名从业者开展新研究,显著提升了工具精确率,并报告了最终精确率(摘要中数值缺失)。论文强调,获取专业反馈对提升规则精确率和扩展规则集至关重要,这直接影响 IaC 安全 linter 等轻量工具的可用性与采纳。

问题
IaC 模板中安全漏洞频发,但现有 IaC 安全 linter 误报率高、不够可靠,难以有效防止漏洞进入生产环境。
方法
访谈专业开发者,收集他们对 Puppet 安全 linter 不精确根因的反馈,并据此调整 7 条规则、新增 3 条规则以构建改进版 linter。
评估
对 131 名从业者开展新一轮研究,评估改进后 linter 的精确率,结果显示精确率显著提升(摘要未给出具体数值)。
原文摘要(Abstract)

Infrastructure-as-Code (IaC) is a technology that enables the management and distribution of infrastructure through code instead of manual processes. In 2020, Palo Alto Network’s Unit 42 announced the discovery of over 199K vulnerable IaC templates through their “Cloud Threat” Report. This report highlights the importance of tools to prevent vulnerabilities from reaching production. Unfortunately, we observed through a comprehensive study that a security linter for IaC scripts is not reliable yet—high false positive rates. Our approach to tackling this problem was to leverage community expertise to improve the precision of this tool. More precisely, we interviewed professional developers to collect their feedback on the root causes of imprecision of the state-of-the-art security linter for Puppet. From that feedback, we developed a linter adjusting 7 rules of an existing linter ruleset and adding 3 new rules. We conducted a new study with 131 practitioners, which helped us improve the tool’s precision significantly and achieve a final precision of . An important takeaway from this paper is that obtaining professional feedback is fundamental to improving the rules’ precision and extending the rulesets, which is critical for the usefulness and adoption of lightweight tools, such as IaC security linters.

链接与引用

DOI 原文 · PDF(开放获取) ·

BibTeX
@inproceedings{paperbot7174,
  title = {Leveraging Practitioners’ Feedback to Improve a Security Linter},
  author = {Sofia Reis and Rui Abreu and Marcelo d'Amorim and Daniel Fortunato},
  booktitle = {ASE},
  year = {2022},
  doi = {10.1145/3551349.3560419}
}