A reported Supabase Storage upload failed with Invalid Compact JWS even after policies were added in the Dashboard. Its author says bucket-scoped SQL policies on storage.objects fixed the upload. That is one debugging account—not evidence that Dashboard policies generally target the wrong place. Supabase’s current documentation supports creating Storage policies through either the Dashboard or SQL.
What happened in the reported upload failure
Lior Karaev describes uploading a CV to a private cvs bucket for the RamenHire job board. The client saw an HTTP 400 response with this body:
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{"statusCode":"403","error":"Unauthorized","message":"Invalid Compact JWS"}The error body’s 403 status and “Invalid Compact JWS” message are distinct from the HTTP 400 observed by the client. Karaev reports trying anonymous INSERT, authenticated SELECT, and authenticated DELETE policies through the Storage UI. The bucket had no file-size or MIME-type limits, and he checked client initialization, filename, path, and content type. The failure persisted until he created bucket-scoped policies directly on storage.objects in the SQL Editor; he says the upload then worked on the first attempt. Read Karaev’s account.
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The outcome is useful as a troubleshooting clue, but it does not establish why that particular request failed. Supabase’s current Storage Quickstart describes creating policies in the Dashboard under Storage > Policies, where users can select the OBJECTS table, as well as creating them with SQL. The article’s claim that the UI could not solve the problem should therefore be treated as an account of one case, not a general rule about the Dashboard.
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Which policies a Storage operation needs
Storage access policies are attached to storage.objects. A bucket restriction is normally expressed in the policy condition, for example bucket_id = 'cvs'. The required operations depend on what the client actually does:
| Operation | Documented policy requirements |
|---|---|
| Upload a new object | INSERT |
| Upload with upsert | INSERT, SELECT, and UPDATE |
These requirements are documented in Supabase’s Storage Access Control guide and, for the Python API, its upload reference. Confirm whether the client is performing a new upload or an upsert before adding policies; a policy for one operation does not automatically authorize the other.
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When an upload may also need SELECT
Supabase documents a specific upload failure with the message new row violates row-level security policy. In that case, an insufficient SELECT policy can stop the Storage API from returning metadata for the inserted object. Supabase recommends SELECT scope that matches the intended INSERT access—not unrestricted read access. This documented case is different from Karaev’s reported Invalid Compact JWS response, so do not assume it explains every failed upload. See Supabase’s 403 upload troubleshooting guide.
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Debug the request before widening access
- Read both the HTTP status and response body. Preserve the exact error string. Supabase lists distinct Storage errors for invalid JWTs, access denial, missing buckets or object keys, and file-size violations in its error-code reference.
- Verify the identity reaching Storage. Check that the request carries the intended user session and role. An anonymous request and an authenticated-user request are not interchangeable, and a broad policy can mask an identity or session problem.
- Check the bucket, object path, and operation. Confirm the target bucket and object key, then determine whether the code is making a new upload or using upsert. Compare the operation to the policy requirements above.
- Inspect the effective policies on
storage.objects. Confirm each policy’s operation, role, and condition. Use SQL when it helps make policy definitions explicit and reviewable; current documentation does not suggest that SQL is inherently more reliable than Dashboard-created policies. - Check database grants as well as RLS policies. Grants and policies are separate controls: a missing grant can prevent access before a policy is evaluated. Supabase explains this distinction in its Row Level Security guide.
- Keep secrets out of client code. Do not put a service key in a browser to bypass RLS. Supabase says service keys bypass RLS and must not be shared publicly.
Scope access to the user and the file’s purpose
A bucket-only condition such as bucket_id = 'cvs' narrows a policy to one bucket, but it does not distinguish one user’s files from another’s. A policy that lets any authenticated user read or delete every object in that bucket may expose private CVs or permit other users’ files to be removed. Likewise, permitting anonymous inserts can leave objects without a durable user identity, complicating ownership and cleanup.
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Design each policy for the actual authorization boundary: the operation, the intended role, the user’s identity, and the permitted object path. Where the application requires a person to access only their own files, use a user-specific path or other appropriate condition, and verify that read and delete permissions are no broader than intended. Supabase notes that owner_id is the current ownership field for policies; the older owner field is deprecated. Ownership metadata can support a policy, but ownership alone does not grant access. See the Storage ownership guide.
Karaev’s sample allowed anonymous inserts and authenticated reads and deletes in the bucket. The author later acknowledged risks around anonymous uploads and authenticated-user scope, including orphaned files, and comments describe moving toward signed upload URLs and tighter policies. Treat that sample as a report of what worked in one setup, not a safe policy to copy unchanged.
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Use Storage APIs for files, SQL for policies
Supabase stores file metadata in Postgres while the file contents live in an underlying storage provider. Its Storage schema documentation recommends treating the Storage schema as read-only for file operations. Create or change access policies on the documented RLS surface, but use the Storage API for upload, copy, move, and delete rather than editing metadata rows directly.
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