Two related authorization gaps in management endpoints:
1. `/project/update` evaluated permission against the team_id supplied in
the request body. By passing `data.team_id` pointing at a team they
admin, a caller could hijack any project — `_check_user_permission_for_project`
was given the attacker's team_object and happily checked admin
membership against that. Drop the team_object kwarg so the helper
re-fetches the existing project's team. Also require admin rights on
the destination team when reassigning a project across teams, so a
team admin cannot shed projects into another team's namespace.
2. `/key/update` accepted any `organization_id` and only checked that
the org existed before applying limits. A caller could thereby point
their key at an arbitrary org. Add `_validate_caller_can_assign_key_org`
which enforces the same membership rule already applied on the
`/key/list` filter path (`validate_key_list_check`); proxy admins and
no-change updates skip the check.
Tests cover both helpers in isolation: existing-team-admin allow,
unrelated-team admin deny, proxy-admin shortcut, org-member allow,
non-member deny, missing user_id deny, no-memberships deny.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Service-account API keys are issued without a `user_id`, and managed
file/batch/vector-store ownership checks compared
`resource.created_by == user_api_key_dict.user_id`. Because Python
evaluates `None == None` as True, any service-account key passed
ownership checks for any resource also created without a user id, and
listing endpoints skipped the `created_by` filter entirely when the
caller had no user id — returning every tenant's records.
Replace the bare equality with an identity-aware helper:
- Admins (PROXY_ADMIN, PROXY_ADMIN_VIEW_ONLY) keep their unscoped view.
- Callers with a `user_id` are scoped to records they created.
- Callers without a `user_id` but with a `team_id` are scoped to records
created within their team via a new `created_by_team_id` column.
- Callers with no admin role and no identifying ids are denied — the
listing path returns an empty page without issuing a query.
Schema migration adds `created_by_team_id` to LiteLLM_ManagedFileTable,
LiteLLM_ManagedObjectTable, and LiteLLM_ManagedVectorStoreTable, plus
indexes for the new filter. Writes in BaseManagedResource and the
enterprise managed_files hook now stamp the column from
`user_api_key_dict.team_id`. Reads in `can_user_access_unified_resource_id`,
`can_user_call_unified_file_id`, `can_user_call_unified_object_id`,
`list_user_resources`, `list_user_batches`, and `get_user_created_file_ids`
all delegate to the new helper.
Tests cover the helper in isolation, the base-class listing/access paths,
and the enterprise file-access hook (including a regression test for the
original `None == None` bypass).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(projects): fire useProjects hook for all authenticated users, not just admins
* fix(routes): add /project/list and /project/info to internal_user_routes allowlist
* fix(projects): use members_with_roles + LiteLLM_UserTable.teams for membership checks
* feat(ui): add "Your Usage" view for admin users on usage page
Admins were forced to use the global usage view with no way to scope it
to their own activity without manually searching for themselves in the
user filter dropdown.
Adds a new "Your Usage" option (admin-only) to the usage view selector.
When selected, it locks the data to the admin's own user_id and hides
the "Filter by user" dropdown.
* feat(ui): wire my-usage view to admin's own user_id in UsagePageView
When usageView is "my-usage", effectiveUserId resolves to the logged-in
admin's own userID. The "Filter by user" dropdown is hidden in this
view (only shown for "global").
* add: screenshots for usage page Your Usage admin fix
* fix(ui): gate useProjects on admin roles to fix failing unit test
* feat(proxy): add /project/list and /project/info to internal user routes
* fix(enterprise): use members_with_roles and litellm_usertable.teams for project access checks
* remove .github screenshots and workflow file from PR
- drop unused Any annotation on register_extra_ui_setting's field
param; type it as FieldInfo and have enterprise callers construct
FieldInfo directly (pydantic.Field's stub reports the default's
type, which doesn't match FieldInfo)
- cache the effective UISettings class and invalidate it inside
register_extra_ui_setting so GET /get/ui_settings does not rebuild
a pydantic model on every request
- annotate _EXTRA_UI_SETTINGS_FIELDS with a concrete
Dict[str, Tuple[Any, FieldInfo]] instead of bare Dict[str, tuple];
the annotation remains Any because pydantic field annotations
include generics (Optional[X], List[X]) that are not instances of
type
Remove the /project/* management endpoints and the enable_projects_ui
admin-settings flag from the OSS litellm package. Project endpoints now
live under litellm_enterprise and are wired through the existing
enterprise router; OSS builds return 404 for every /project/* route.
The enable_projects_ui UI flag is registered back onto UISettings via a
small extension registry when the enterprise package is imported, so the
admin toggle and downstream key/sidebar gating continue to work in
enterprise builds. On OSS, explicit PATCH attempts with the flag return
403 with a clear enterprise-only message instead of being silently
dropped.
Pydantic request/response types (NewProjectRequest, UpdateProjectRequest,
DeleteProjectRequest, NewProjectResponse) stay in litellm/proxy/_types.py
because management_endpoints/common_utils.py and pydantic-shape tests
import them. LiteLLM_ProjectTable and all FK columns in schema.prisma
are unchanged.
* fix: batch-limit stale managed object cleanup to prevent 300K row UPDATE (#25257)
* Add STALE_OBJECT_CLEANUP_BATCH_SIZE constant
Configurable batch limit (default 1000) for stale managed object cleanup,
preventing unbounded UPDATE queries from hitting 300K+ rows at once.
* Batch-limit stale managed object cleanup with single bounded SQL query
Two fixes to _cleanup_stale_managed_objects:
1. Replace unbounded update_many with a single execute_raw using a
subquery LIMIT, capping each poll cycle to STALE_OBJECT_CLEANUP_BATCH_SIZE
rows. Zero rows loaded into Python memory — everything stays in Postgres.
Uses the same PostgreSQL raw-SQL pattern as spend_log_cleanup.py
(the proxy requires PostgreSQL per schema.prisma).
2. Extract _expire_stale_rows as a separate method for testability.
Keeps the file_purpose='response' filter to avoid incorrectly expiring
long-running batch or fine-tune jobs that legitimately exceed the
staleness cutoff.
* docs: add STALE_OBJECT_CLEANUP_BATCH_SIZE to env vars reference
* test: remove deprecated embed-english-v2.0 cohere embedding tests
- Add Prometheus metrics for managed batch and file operations
- Track batch creation, file size, duration, and deletion events
- Add CheckBatchCost polling metrics (jobs polled/processed, errors)
- Record metrics in managed_files hook and check_batch_cost utility
- Metrics include labels for model, provider, user, and status
Made-with: Cursor
- Promote _fetch_managed_vector_stores_by_uuids from @staticmethod to a module-level
async helper get_managed_vector_store_rows_by_uuids, following the same standalone
helper pattern as get_team_object / get_key_object so the hot-path DB read is a
named importable function rather than an inline prisma_client.db.* call
- Pass no-log=True to both inner _call_aresponses sub-calls so they do not fire
independent billing/monitoring callbacks; cost is accumulated in the synthesized
response's _hidden_params for the outer responses() call
- Add test_H11b covering the primary queries (plural array) function-tool schema,
complementing H11 which exercises only the backward-compat singular query path
Made-with: Cursor
- Re-add should_use_emulated_file_search() to emulated_handler.py so H5/H6/H7/H13 tests don't fail with ImportError
- Remove per-file-id deduplication from _build_search_results_for_include so all chunks are returned (matching OpenAI native file_search behaviour); update test_H14 to assert 2 results
- Extract raw prisma DB query in check_vector_store_ids_access into a static _fetch_managed_vector_stores_by_uuids helper so the hot request path uses a named, testable function instead of an inline prisma_client.db.* call
- Remove developer-local path from test module docstring
Made-with: Cursor
The retrieve_batch endpoint sets batch status to "complete" but never set
batch_processed=True, permanently blocking file deletion. CheckBatchCost
(the safety net) also excluded completed batches from its primary query,
so batch_processed was never set by either path.
Three fixes:
1. update_batch_in_database sets batch_processed=True when status reaches
"complete", with old-schema fallback retry
2. CheckBatchCost primary query no longer excludes complete/completed
(batch_processed=False filter prevents reprocessing)
3. retrieve_batch early-return now includes "complete" (DB-normalized
spelling) to avoid unnecessary provider re-polls
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(proxy): cap managed-object poll size + expire stale rows + kill-switch flag to prevent OOM/Prisma connection loss
* fix(constants): simplify PROXY_BATCH_POLLING_ENABLED readability
* docs+test: document new polling env vars, add pagination+stale-cleanup tests
* fix: exclude stale_expired from batch poll queries; fix update_many assertions in tests
* fix: scope stale cleanup to file_purpose, fix file_object mocks, add CheckBatchCost tests
* fix: avoid duplicate cost logging in fallback path; guard integer constants against zero/negative values
* fix: cache _has_batch_processed_column; guard cleanup from aborting poll; narrow fallback except
* fix: add complete/completed to primary query not_in; fix vacuous test assertion
- Primary find_many was missing "complete" and "completed" in its not_in
filter, creating asymmetry with the fallback query. A job whose status
was set to "complete" but whose batch_processed flag update failed would
be silently re-fetched and re-processed every cycle, emitting duplicate
cost logs.
- test_fallback_completion_update_omits_batch_processed patched
_is_base64_encoded_unified_file_id to return None, causing an immediate
continue — so update() was never called and the assertion looped over an
empty list (vacuously true). Rewrote the test to mock the full
completion pipeline, verify update() is called exactly once, and assert
batch_processed is absent from the update data.
- Added symmetric test (primary path) proving batch_processed IS included
when the column exists.
Made-with: Cursor
- Remove unused `completed_jobs` list (dead code after per-job update refactor)
- Wrap DB update in try/except to prevent one failed update from aborting remaining jobs
- Add test assertions verifying batch_processed, status, and file_object are written to DB
CheckBatchCost poller updated the status column but not the file_object
JSON column. The list_batches endpoint reads status from file_object,
so batches appeared stuck in "validating" even after Azure reported
them as completed. Now update file_object alongside status in the
per-job DB write.
- Fix object_team_id + object_key_hash combining incorrectly as OR — each
filter now adds an AND clause wrapping an internal OR over before_value
and updated_values, so both conditions must be satisfied simultaneously
- Rename helper to _build_json_field_or_condition to reflect its purpose
- Remove allTeams from AuditLogsProps and its call site in index.tsx
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Replace client-side full-fetch loop with single react-query call using
keepPreviousData; remove 5-second polling
- All filters (object ID, action, table, changed_by, team ID, key hash)
now passed as query params to the backend
- Add object_team_id and object_key_hash params to /audit endpoint using
Prisma JSON path filtering (PostgreSQL) to search inside before_value
and updated_values JSON columns
- Migrate table from custom TanStack DataTable to AntD Table with
server-side pagination
- Replace inline row expansion with a right-side AntD Drawer showing
metadata and before/after diff
- Refactor uiAuditLogsCall to accept a structured options object
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
batch_cost_calculator only checked the global cost map, ignoring
deployment-level custom pricing (input_cost_per_token_batches etc.).
Add optional model_info param through the batch cost chain and pass
it from CheckBatchCost.
- route_llm_request.py: add acancel_batch and afile_delete to route_type Literal
- router.py: add SearchToolInfoTypedDict and search_tool_info to SearchToolTypedDict
- gemini/files/transformation.py: fix validate_environment signature to match base class
- responses transformation.py: fix Dict type annotations to use int instead of Optional[int]
- vector_stores/endpoints.py: add team_id and user_id to LiteLLM_ManagedVectorStoresTable constructor
Co-authored-by: shin-bot-litellm <shin-bot-litellm@users.noreply.github.com>
