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| GitGuardian id | GitGuardian status | Secret | Commit | Filename | |
|---|---|---|---|---|---|
| 9429425 | Triggered | Generic Password | 29f8f78 | django/.env.example | View secret |
🛠 Guidelines to remediate hardcoded secrets
- Understand the implications of revoking this secret by investigating where it is used in your code.
- Replace and store your secret safely. Learn here the best practices.
- Revoke and rotate this secret.
- If possible, rewrite git history. Rewriting git history is not a trivial act. You might completely break other contributing developers' workflow and you risk accidentally deleting legitimate data.
To avoid such incidents in the future consider
- following these best practices for managing and storing secrets including API keys and other credentials
- install secret detection on pre-commit to catch secret before it leaves your machine and ease remediation.
🦉 GitGuardian detects secrets in your source code to help developers and security teams secure the modern development process. You are seeing this because you or someone else with access to this repository has authorized GitGuardian to scan your pull request.
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Le jeton était un jeton de test généré par l'interface de Supabase. https://supabase.com/docs/guides/self-hosting/docker |
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The database, created by Pytest on a local PG server, was missing Supabase's specific structure used in production. For example, the `auth` schema with the `users` table was first created by a conftest.py and then by a signal. It was also missing tables, functions and triggers created manually on Supabase before Django migrations were used. The more we import in Django the production structure, the more we need a database that acts like the real one. The test database is now created in a Docker container whose image is managed directly by Supabase. See the `docker-compose.yml`. The file `prod_schema_before_django_migrations.sql` references how the database structure was before we start to use Django. It is used as a seed file to populate the test database. A mise command starts all the above and run migrations (start:tests). Then Pytest uses the test database (thanks to the tests config).
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Suite :
pytest-envau profit de l'optionpytest --dspytest --covpar défaut pour une meilleure lisibilité de la suite de test.