examples

Storage Object Enumeration examples

These examples show how Storage Object Enumeration problems ship in real apps — and what fixes actually work when tested via direct API access.

Why Storage Object Enumeration examples matter

Enumeration turns small misconfigurations into large leaks because once keys are known attackers can download many files.

Example	Summary	URL
Predictable prefix keys leak user files	Predictable prefixes make brute-force enumeration easy.	/examples/storage-object-enumeration/predictable-prefix-keys-leak-user-files
Storage listing enables object enumeration	Allowing bucket listing handed attackers a catalog of object keys.	/examples/storage-object-enumeration/storage-listing-enables-object-enumeration

Examples are most useful when you can translate them into a repeatable fix pattern. This table highlights the “why” behind each fix:

Example	Root cause	Fix pattern	URL
Predictable prefix keys leak user files	Predictable keys turned identity into filenames, so attackers guessed prefixes and downloaded files when weak reads existed.	Switch to random UUID keys, keep the bucket private, and generate signed URLs only after verifying ownership.	/examples/storage-object-enumeration/predictable-prefix-keys-leak-user-files
Storage listing enables object enumeration	Listing became a discovery API, so attackers collected keys and abused any permissive read rule.	Remove listing permissions, implement a backend listing endpoint that returns only authorized objects, and serve downloads via signed URLs.	/examples/storage-object-enumeration/storage-listing-enables-object-enumeration

Across these examples, the highest-leverage fixes share a theme: remove direct client access and make verification repeatable.

Backend-only access for sensitive operations (server endpoints enforce authorization).
Least-privilege grants: revoke broad privileges from anon/authenticated.
Small, testable policies if you intentionally keep client access — avoid complex conditions.
A verification step that proves direct access fails (not just that the UI hides data).

A direct API call returns rows/files even when the UI is supposed to restrict them.
RLS/policies exist, but access still succeeds (often because RLS is disabled or policies are too broad).
Permissions depend on the client behaving “nicely” (UI checks) rather than the database enforcing access.
After a migration, access behavior changes unexpectedly (drift).

Reproduce the issue once using direct API access (anon/authenticated) so you know it’s real.
Apply the fix pattern (backend-only access + least privilege) using a template.
Repeat the same direct access call and confirm it now fails.
Confirm the app still works via backend endpoints for authorized users.
Re-scan after the fix and add a drift guard for the next migration.

Re-run the same direct access test after every migration that touches auth, policies, grants, Storage, or functions.
Keep a short inventory of sensitive resources and treat them as server-only by default.
Review new tables/buckets/functions in code review with an access-control checklist.
If you intentionally allow client access, document the policy rationale and add tests for it.

If you like having a repeatable “proof”, add a small set of SQL checks to your process.

Confirm RLS status for tables involved (enabled/forced where appropriate).
List policies and read them as plain language: who can do what under what condition?
Audit grants to anon/authenticated and PUBLIC for tables, views, and functions tied to this topic.
If Storage/RPC is involved, explicitly audit bucket settings and EXECUTE grants.

These checks complement (not replace) the direct access tests shown in the examples.

If you’re here because you found this topic in a scan, the fastest path depends on whether the fix is a small config change or a workflow change.

Choose a template when you need a copy/paste change plus verification (tighten a policy/grant/bucket setting).
Choose a conversion when you need to change an access model end-to-end (unsafe → backend-only) with example transformations.
Choose an integration when the fix is a workflow pattern you’ll repeat (signed URLs, server-only RPC, backend endpoints).

If you’re unsure, start with the smallest template that removes direct client access, then add integrations for durability.

Teams often “fix” a topic but can’t prove it later. Save a few small artifacts so you can re-verify after migrations:

The direct access request you used before the fix (and the expected denial after).
A short boundary statement (who can access what, through which server endpoint).
The change you applied (policy/grant/bucket setting/EXECUTE revoke) and why.
The drift guard you’ll run after migrations (scan, checklist query, or release checklist item).

Glossary: Storage Object Enumeration → /glossary/storage-object-enumeration
Template: Make a bucket private + serve files with signed URLs → /templates/storage-safety/make-bucket-private-signed-urls

One fixed example is great — but the real win is preventing drift.

Write a one-sentence boundary statement (who can access what, through which server path).
Keep the one direct access test you used before the fix (and expect it to fail after).
Re-run the same test after migrations that touch policies, grants, buckets, or functions.

If you can re-run the test and it still fails, you’ve turned a one-time fix into a durable control.