# Reporting issues in Weblate Weblate [issue tracker](https://github.com/WeblateOrg/weblate/issues) is hosted at GitHub. Feel welcome to report any issues you have or suggest improvements for Weblate there. There are various templates prepared to comfortably guide you through the issue report. #### NOTE If what you have found is a security issue in Weblate, please see [Product vulnerability reports](https://docs.weblate.org/no/latest/security/issues.md#security). If you are not sure about your bug report or feature request, you can try [Weblate discussions](https://docs.weblate.org/no/latest/contributing/index.md#discussions). ## Accessibility issues Accessibility problems should use the accessibility issue template. A good report includes the affected page or workflow, reproduction steps, expected and actual behavior, browser and operating system, assistive technology in use, and whether the problem occurs with keyboard-only navigation. Maintainers label accessibility reports with `accessibility`. During triage, use the impact on core workflows and available workarounds to choose priority: - Blocker: a core workflow cannot be completed. - High: a core workflow is difficult, but a workaround exists. - Medium: a non-core workflow is difficult or inconsistent. - Low: a minor issue or polish problem that does not block the workflow. See `ACCESSIBILITY.md` for Weblate’s accessibility target and reporting guidance. ## Using AI to create issues If you asked an AI tool to find problems in Weblate or its modules, you **must** make sure to reveal this fact in your report. You must also double-check the findings carefully before reporting them to us to validate that the issues are indeed existing and working exactly as the AI says. AI-based tools frequently generate inaccurate or fabricated results. It is *rarely* a good idea to just copy and paste an AI-generated report to the project. Those generated reports typically are too wordy and rarely to the point (in addition to the common fabricated details). If you actually discover an issue with an AI and you have verified it yourself to be true, write the report yourself and explain the issue as you have learned it. This makes sure the AI-generated inaccuracies and invented issues are filtered out early before they waste more people’s time. As we take security reports seriously, we investigate each report with priority. This work is both time- and energy-consuming and pulls us away from doing other meaningful work. Fake and otherwise made-up security issues effectively prevent us from doing real project work and make us waste time and resources. We ban users immediately who submit made-up fake reports to the project. ## Issues lifecycle