NLNet Labs LLM Policy
摘要
NLNet Labs 发布了其组织与项目中使用大语言模型（LLM）的政策，核心要求包括：代码和文档贡献必须由人类撰写，禁止包含 LLM 等概率工具生成的内容（唯一的例外是漏洞或缺陷报告中可附带 LLM 建议的修复，以帮助定位问题）；在与项目互动时（如提交 issue、发送漏洞报告、在社区论坛发帖等），必须披露是否使用了 LLM；鼓励披露机器翻译的使用，但因其生成特性可能混淆讨论而不鼓励使用 LLM 翻译；允许将 LLM 用于代码检查、分析或审查，但使用者需对 LLM 的输出负责，必须理解并验证信息的正确性。政策还给出了两个示例：LLM 辅助的漏洞报告流程，以及 PR 创建中禁止 LLM 生成内容、要求用自己语言描述且新功能需先与项目沟通。违反政策的内容可能被关闭或删除。
荐读理由
反价值#2，NLNet Labs LLM Policy 属于产品发布稿/政策公关稿，严格禁止PR、issue、论坛帖采用任何LLM生成内容，只许人类亲自撰写且披露使用
原文
LLM POLICY
Revised 26 June 2026
We restrict how Large Language Models (LLMs) can be used in the context of our organisation and our projects. If a submission (e.g. PR, issue, comment, forum post, etc.) does not comply with this policy, we may close or delete it without prior notice.
Note
In addition to this policy, you must also comply with our code of conduct and the relevant CONTRIBUTING.md file of the project.
Policy
No output of LLMs in code or documentation
We require all code and documentation contributions to be authored by a human. You must not include content generated by LLMs or other probabilistic tools.
As an exception to this rule, a suggested fix generated by an LLM as part of a vulnerability or bug report may be included, because it can help pinpoint the underlying issue during triage.
Disclose LLM use
We want to interact with humans, not with LLMs. In your interactions with us, be respectful of our time, and disclose the use of an LLM. This includes opening issues, sending vulnerability reports, and posting on our community forum.
Translation can be helpful if English is not your native language. If you use machine translation when communicating with us, we encourage you to disclose such use to us so that both sides are aware of possible miscommunication as a result of mistranslation. Alternatively, you could also write in your native language if you cannot assess the correctness of the translation.
Use of LLM translation is discouraged based on their generative attributes that would most likely confuse rather than ease the discussion.
LLM output remains your responsibility
Your use of LLMs for linting, analysis or review is permitted under this policy. However, you remain responsible for the output of an LLM. If an LLM assists you in finding or analysing an issue, you remain responsible to understand and verify the correctness of the information you share with us.
Examples
LLM-assisted vulnerability reporting
We accept reports of vulnerabilities found with LLMs. With your report, you can include an LLM suggested fix to help us pinpoint the issue. To comply with this policy, after the LLM finds an issue, you as the human contributor verify the issue and the estimated severity. Then, when you send a report to sep@nlnetlabs.nl you must disclose the use of an LLM.
See the security report page for more information on reporting vulnerabilities to us.
PR creation
We do not accept LLM-generated contributions. Any code you submit cannot be generated by an LLM. When you open a PR, use your own words and be concise in the PR description.
In general, you should not open PRs for new features without talking to us first. If you have ideas on how our software could change to accommodate your use-case, please share your own thoughts on our community forum.
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