NLNet Labs LLM Policy

LLM POLICY Revised 26 June 2026 大语言模型（LLM）政策（2026年6月26日修订）

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. 我们对大语言模型（LLM）在我们组织及项目中的使用方式进行了限制。如果提交的内容（如 PR、Issue、评论、论坛帖子等）不符合本政策，我们可能会在不另行通知的情况下将其关闭或删除。

Note: In addition to this policy, you must also comply with our code of conduct and the relevant CONTRIBUTING.md file of the project. 注意：除本政策外，您还必须遵守我们的行为准则以及相关项目的 CONTRIBUTING.md 文件。

Policy

政策

No output of LLMs in code or documentation 代码或文档中不得包含 LLM 生成的内容

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. 我们要求所有代码和文档贡献必须由人工编写。您不得包含由 LLM 或其他概率性工具生成的内容。作为此规则的例外，若 LLM 生成的修复建议是漏洞或 Bug 报告的一部分，则可以包含在内，因为这有助于在分类过程中查明根本问题。

Disclose LLM use 披露 LLM 的使用情况

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. 我们希望与人类互动，而非与 LLM 互动。在与我们交流时，请尊重我们的时间，并披露 LLM 的使用情况。这包括提交 Issue、发送漏洞报告以及在我们的社区论坛发帖。

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. 如果英语不是您的母语，翻译工具可能会有所帮助。如果您在与我们沟通时使用了机器翻译，我们鼓励您向我们披露，以便双方都能意识到因翻译错误可能导致的沟通偏差。或者，如果您无法评估翻译的准确性，也可以直接使用您的母语书写。我们不建议使用 LLM 进行翻译，因为其生成式属性很可能会造成困扰，而非简化讨论。

LLM output remains your responsibility LLM 的输出结果由您自行负责

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. 根据本政策，允许您使用 LLM 进行代码检查（linting）、分析或审查。但是，您仍需对 LLM 的输出结果负责。如果 LLM 协助您发现或分析了问题，您仍有责任理解并核实您与我们分享的信息的准确性。

Examples

示例

LLM-assisted vulnerability reporting LLM 辅助的漏洞报告

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. 我们接受通过 LLM 发现的漏洞报告。在报告中，您可以包含 LLM 提供的修复建议，以帮助我们定位问题。为符合本政策，在 LLM 发现问题后，作为人类贡献者的您必须核实该问题及其预估的严重程度。随后，在向 sep@nlnetlabs.nl 发送报告时，您必须披露 LLM 的使用情况。有关向我们报告漏洞的更多信息，请参阅安全报告页面。

PR creation PR 创建

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. 我们不接受 LLM 生成的贡献。您提交的任何代码都不得由 LLM 生成。在创建 PR 时，请使用您自己的语言，并保持 PR 描述简洁。通常情况下，在未与我们沟通之前，请勿针对新功能提交 PR。如果您对我们的软件如何改进以适应您的用例有任何想法，请在我们的社区论坛分享您的见解。