Open WebUI's collection ACL accepted any unknown name as a
legacy/ephemeral collection. In Milvus multi-tenancy mode that name
becomes the `resource_id` and is interpolated unescaped into a SQL-like
Milvus expression — `resource_id == '<name>'` — so a name like
x' or resource_id != '' or resource_id == 'x
turns the filter into a tautology and returns every tenant's chunks
from the shared collection.
All collection names Open WebUI generates are UUIDs, SHA-256 hex
digests, or fixed-prefix variants of those — they all fit
[A-Za-z0-9_-]. Add a strict format check in
filter_accessible_collections (utils.py) that drops any name outside
that set before any ACL or vector-store lookup, applied even on the
admin bypass path. _validate_collection_access then surfaces the dropped
name as a 403.
As defense in depth, MilvusClient now validates resource_id at every
expression-construction site and escapes single quotes / backslashes in
any other string interpolated into a filter (delete ids, metadata
filter values). Non-string filter values are typed-checked instead of
str()-formatted.
Co-authored-by: Claude <noreply@anthropic.com>
validate_url() in retrieval/web/utils.py only validates the initial URL.
The HTTP clients used downstream (sync requests, sync requests via the
parent WebBaseLoader._scrape, aiohttp via load_url_image) followed 3xx
redirects by default and did not re-validate the redirect target against
the private-IP / metadata-IP block list. An authenticated user could
submit a public URL that 302-redirected to an internal address (RFC1918,
127.0.0.1, 169.254.169.254, etc.) and the redirected response was returned
to them, enabling SSRF reads of internal services and cloud metadata.
Three call sites needed allow_redirects=False to match the policy already
enforced on the async _fetch() path:
- SafeWebBaseLoader: override requests_kwargs in __init__ so that the
inherited synchronous _scrape() path passes allow_redirects=False to
self.session.get() (the parent WebBaseLoader uses requests' default
allow_redirects=True).
- get_content_from_url (retrieval/utils.py): pass allow_redirects=False
on the streamed requests.get(...) call.
- load_url_image (routers/images.py, image-edits endpoint): pass
allow_redirects=False on the aiohttp session.get(...) call.
Reports consolidated under GHSA-rh5x-h6pp-cjj6:
- GHSA-rh5x-h6pp-cjj6 (tenbbughunters / Tenable) - sync _scrape
- GHSA-5vxg-6gmv-m2qr (YLChen-007) - load_url_image
- GHSA-hf76-c83f-63w2 (tempcollab) - aiohttp _fetch (already fixed)
- GHSA-h55f-h5fh-mvm4 (sneaXOR) - get_content_from_url
Add configurable reranker batch size (env var RAG_RERANKING_BATCH_SIZE,
default 32) following the same pattern as RAG_EMBEDDING_BATCH_SIZE.
- config.py: PersistentConfig for RAG_RERANKING_BATCH_SIZE
- main.py: import, state init, pass to get_reranking_function
- colbert.py: accept batch_size param in predict() (was hardcoded 32)
- utils.py: get_reranking_function passes batch_size at call time
- retrieval.py: expose in config GET/POST endpoints and ConfigForm
- Documents.svelte: add Reranking Batch Size input in admin settings
Closes#23730
* fix(retrieval): offload sync VECTOR_DB_CLIENT calls in async paths via AsyncVectorDBClient
The vector DB backends (Chroma, pgvector, Qdrant, Milvus, Pinecone,
Weaviate, …) are uniformly synchronous and their methods perform
blocking network or disk I/O. Multiple async route handlers and helpers
were calling them directly on the event loop — file processing,
memories, knowledge bases, hybrid search bookkeeping — so a single
upsert/delete/search would freeze every other in-flight request for the
duration of the call.
Introduce `AsyncVectorDBClient`, a thin async facade that wraps the
existing sync client and dispatches each method through
`asyncio.to_thread`. It mirrors `VectorDBBase` exactly and forwards
*args/**kwargs so backend-specific extra parameters keep working.
Update every async-context call site (routers/retrieval, routers/files,
routers/memories, routers/knowledge, retrieval/utils,
tools/builtin) to await `ASYNC_VECTOR_DB_CLIENT` instead of calling the
sync client directly. Two helpers that were sync-only also acquire
async siblings or are awaited via `asyncio.to_thread` at their async
call site (`remove_knowledge_base_metadata_embedding`,
`get_all_items_from_collections`, `query_doc`).
The original sync `VECTOR_DB_CLIENT` is unchanged, so callers that
already run inside `run_in_threadpool` (e.g. `save_docs_to_vector_db`
and the sync `query_doc`/`get_doc` helpers) are unaffected.
https://claude.ai/code/session_01JSr4NZSskEUQvoJnavVXh8
* fix(retrieval): restore explicit AsyncVectorDBClient signatures matching VectorDBBase
Per PR review: the original *args/**kwargs forwarding lost type
safety and IDE/static-analysis support. Restore explicit signatures
that mirror VectorDBBase exactly, so:
* Bad kwargs fail at the facade boundary instead of inside the
worker thread (where the resulting TypeError tends to be
swallowed by surrounding `try/except`).
* IDE autocomplete and static analysis work as expected.
* The stated intent ("mirror VectorDBBase exactly") now holds at
the API contract level, not just behaviourally.
While doing this, surface a pre-existing bug in
`delete_entries_from_collection` that the stricter typing flagged:
the call passed `metadata={'hash': hash}` which is not a parameter
on `VectorDBBase.delete` nor any backend. The TypeError raised
inside the sync delete was silently swallowed by `except Exception`
so the endpoint always reported `{'status': False}` for every
request instead of actually deleting matching vectors. Replace with
`filter=...` to do what the endpoint name promises.
The thorough review's other note (no concurrency/backpressure on
the shared default threadpool) is intentionally not addressed here:
asyncio.to_thread on the shared executor is the right primitive for
this use case; per-domain bounded executors would add lifecycle
complexity disproportionate to the problem and the loop is no
longer blocked, which was the actual bug.
https://claude.ai/code/session_01JSr4NZSskEUQvoJnavVXh8
* fix(retrieval): parallelize hybrid-search collection prefetch; document async facade contracts
Address PR review findings:
1. Hybrid-search prefetch was sequential
`query_collection_with_hybrid_search` previously awaited
`ASYNC_VECTOR_DB_CLIENT.get(name)` once per collection in a for
loop. Each call already off-loaded to a worker thread, but
awaiting them serially meant total prefetch latency scaled
linearly with the number of collections. Run them concurrently
with `asyncio.gather` so multi-collection queries actually
benefit from the threadpool. Per-collection exception handling
is preserved by wrapping each fetch in a small helper that
logs and returns `(name, None)` on failure, so a single bad
collection cannot poison the whole gather.
2. Document the thread-safety expectation explicitly
The facade now formally states what was always implicit: the
sync `VECTOR_DB_CLIENT` is shared across worker threads, so the
underlying backend driver must be thread-safe. This is not a
new exposure — `save_docs_to_vector_db` already called the sync
client from `run_in_threadpool`. Adding a global lock here
would defeat the responsiveness the facade exists to provide;
backends that cannot tolerate concurrent access should grow
their own internal serialization.
3. Document the API-surface choice and `.sync` escape hatch
The strict `VectorDBBase` mirror was a deliberate choice (the
previous `*args/**kwargs` revision let a `metadata=` typo
silently break an endpoint). Document it, and call out the
`.sync` escape hatch with an example for callers that genuinely
need a backend-specific parameter not on `VectorDBBase`.
https://claude.ai/code/session_01JSr4NZSskEUQvoJnavVXh8
* fix(retrieval): guard /delete against null file.hash and let HTTPException reach the client
Address PR review finding on the `metadata=` → `filter=` change in
`delete_entries_from_collection`.
The new `filter={'hash': hash}` query was correct for files that
have a hash, but did not handle `file.hash is None` (unprocessed,
failed, or legacy records). The match semantics of a null filter
value are backend-dependent — some ignore the key entirely, some
treat it as "metadata field absent" and match every such row — so
issuing the query risked deleting unrelated entries.
* Reject `hash is None` up front with a 400 explaining the file
has no hash to target.
* Narrow the surrounding `except Exception` so it no longer
swallows `HTTPException`. Without this fix the new 400 (and the
pre-existing 404 for missing files) would be silently re-shaped
into `{'status': False}` and the caller could not distinguish a
bad-request input from a backend error.
https://claude.ai/code/session_01JSr4NZSskEUQvoJnavVXh8
---------
Co-authored-by: Claude <noreply@anthropic.com>
`raise "string"` in Python raises TypeError instead of the intended
error, making error messages confusing and debugging difficult.
Co-authored-by: gambletan <ethanchang32@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Timothy Jaeryang Baek