CVE-2026-87017

Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform. From 0.7.0 until 0.11.1, the built-in knowledge search tool passed the caller's readable knowledge identifiers through a metadata filter, but the search methods in eleven shipped vector backends ignored that filter. An authenticated user on an affected backend could enumerate the identifiers, names, and descriptions of inaccessible knowledge bases from the shared collection, although the associated document text remained in separate collections. This issue is fixed in version 0.11.1.

Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform. From 0.7.0 until 0.11.1, the built-in knowledge search tool passed the caller's readable knowledge identifiers through a metadata filter, but the search methods in eleven shipped vector backends ignored that filter. An authenticated user on an affected backend could enumerate the identifiers, names, and descriptions of inaccessible knowledge bases from the shared collection, although the associated document text remained in separate collections. This issue is fixed in version 0.11.1.

Summary

The built-in knowledge search tool returns knowledge bases the calling user has no access to. The tool works out which knowledge bases the caller may read and hands that set to the vector store as a search filter, and that filter is the only access control on the path. Most of the shipped vector backends accept the filter argument on their search method and never apply it, so the search returns matches from every knowledge base in the shared collection. The sibling query method on those same backends does apply a filter, which is why the omission is invisible from the calling code.

Preconditions

• The deployment must use one of the affected vector backends, selected with VECTOR_DB, which defaults to chroma. Chroma applies the filter, so a default deployment is not affected.
• Eleven of the fifteen shipped backends ignore the filter: both Qdrant clients, Elasticsearch, OpenSearch, both Milvus clients, openGauss, Oracle 23ai, Pinecone, S3 Vectors and Weaviate. Chroma, pgvector, MariaDB and Valkey apply it and were never affected.
• The caller needs a model that can call tools, with the knowledge built-in tools left enabled, which is the default, and with no knowledge attached to the model itself. No elevated role or permission is required.
• At least one knowledge base must exist that the caller cannot otherwise read.

Impact

A user receives the identifier, name and description of knowledge bases that were never shared with them, and chooses how many results to ask for, so the set can be enumerated by varying the query. The affected collection stores one entry per knowledge base whose text is its name and description, so where those values are themselves sensitive, for example when they name a customer, a project or an investigation, that disclosure is the loss.

The exposure is confined to that metadata. Document text lives in separate per-knowledge-base collections reached by a different call that is scoped by collection rather than by this filter, so stored documents are not returned by this path, and no write access is gained. Because the default backend is unaffected, the population at risk is operators who deliberately moved to an external vector store, which in practice means larger deployments.

Fix

Fixed in 0.11.1 by 1d6d4e6e6. Every affected backend now applies the caller-supplied filter in its search method, combined with the collection or tenant scoping that method already performed. Where a backend's filter builder could express only single-value equality it was extended to express set membership, since that is the form the knowledge tool sends, and a filter using any other operator is now rejected rather than dropped. Upgrading is sufficient and no configuration change is required. Deployments on Chroma, pgvector, MariaDB or Valkey were never affected and need no action.

Root cause

• The search method of each affected vector client, which declares a filter parameter and never references it.
• The built-in knowledge search tool, which relies on that filter as its only access check.
• Present from 0.7.0, the release that introduced the tool, through 0.11.0.

Each client exposes a search method and a query method that appear interchangeable from the calling side and differ in whether the caller's filter survives. Search built its request with collection or tenant scoping only, so it was correctly scoped to the collection and entirely unscoped within it. The knowledge tool resolves the caller's readable knowledge bases correctly and passes them down, then reads the results without rechecking them, on the reasonable assumption that a filter handed to a vector store is applied. Because the access decision was delegated wholly to a parameter that most implementations discarded, the caller had no way to observe that it received more than it asked for.

That the same omission repeated across most backends points at the shared interface rather than at any one client: the base class defines the…

Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform. From 0.7.0 until 0.11.1, the built-in knowledge search tool passed the caller's readable knowledge identifiers through a metadata filter, but the search methods in eleven shipped vector backends ignored that filter. An authenticated user on an affected backend could enumerate the identifiers, names, and descriptions of inaccessible knowledge bases from the shared collection, although the associated document text remained in separate collections. This issue is fixed in version 0.11.1.

Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform. From 0.7.0 until 0.11.1, the built-in knowledge search tool passed the caller's readable knowledge identifiers through a metadata filter, but the search methods in eleven shipped vector backends ignored that filter. An authenticated user on an affected backend could enumerate the identifiers, names, and descriptions of inaccessible knowledge bases from the shared collection, although the associated document text remained in separate collections. This issue is fixed in version 0.11.1.

Summary

The built-in knowledge search tool returns knowledge bases the calling user has no access to. The tool works out which knowledge bases the caller may read and hands that set to the vector store as a search filter, and that filter is the only access control on the path. Most of the shipped vector backends accept the filter argument on their search method and never apply it, so the search returns matches from every knowledge base in the shared collection. The sibling query method on those same backends does apply a filter, which is why the omission is invisible from the calling code.

Preconditions

• The deployment must use one of the affected vector backends, selected with VECTOR_DB, which defaults to chroma. Chroma applies the filter, so a default deployment is not affected.
• Eleven of the fifteen shipped backends ignore the filter: both Qdrant clients, Elasticsearch, OpenSearch, both Milvus clients, openGauss, Oracle 23ai, Pinecone, S3 Vectors and Weaviate. Chroma, pgvector, MariaDB and Valkey apply it and were never affected.
• The caller needs a model that can call tools, with the knowledge built-in tools left enabled, which is the default, and with no knowledge attached to the model itself. No elevated role or permission is required.
• At least one knowledge base must exist that the caller cannot otherwise read.

Impact

A user receives the identifier, name and description of knowledge bases that were never shared with them, and chooses how many results to ask for, so the set can be enumerated by varying the query. The affected collection stores one entry per knowledge base whose text is its name and description, so where those values are themselves sensitive, for example when they name a customer, a project or an investigation, that disclosure is the loss.

The exposure is confined to that metadata. Document text lives in separate per-knowledge-base collections reached by a different call that is scoped by collection rather than by this filter, so stored documents are not returned by this path, and no write access is gained. Because the default backend is unaffected, the population at risk is operators who deliberately moved to an external vector store, which in practice means larger deployments.

Fix

Fixed in 0.11.1 by 1d6d4e6e6. Every affected backend now applies the caller-supplied filter in its search method, combined with the collection or tenant scoping that method already performed. Where a backend's filter builder could express only single-value equality it was extended to express set membership, since that is the form the knowledge tool sends, and a filter using any other operator is now rejected rather than dropped. Upgrading is sufficient and no configuration change is required. Deployments on Chroma, pgvector, MariaDB or Valkey were never affected and need no action.

Root cause

• The search method of each affected vector client, which declares a filter parameter and never references it.
• The built-in knowledge search tool, which relies on that filter as its only access check.
• Present from 0.7.0, the release that introduced the tool, through 0.11.0.

Each client exposes a search method and a query method that appear interchangeable from the calling side and differ in whether the caller's filter survives. Search built its request with collection or tenant scoping only, so it was correctly scoped to the collection and entirely unscoped within it. The knowledge tool resolves the caller's readable knowledge bases correctly and passes them down, then reads the results without rechecking them, on the reasonable assumption that a filter handed to a vector store is applied. Because the access decision was delegated wholly to a parameter that most implementations discarded, the caller had no way to observe that it received more than it asked for.

That the same omission repeated across most backends points at the shared interface rather than at any one client: the base class defines the…

Summary

The built-in knowledge search tool returns knowledge bases the calling user has no access to. The tool works out which knowledge bases the caller may read and hands that set to the vector store as a search filter, and that filter is the only access control on the path. Most of the shipped vector backends accept the filter argument on their search method and never apply it, so the search returns matches from every knowledge base in the shared collection. The sibling query method on those same backends does apply a filter, which is why the omission is invisible from the calling code.

Preconditions

• The deployment must use one of the affected vector backends, selected with VECTOR_DB, which defaults to chroma. Chroma applies the filter, so a default deployment is not affected.
• Eleven of the fifteen shipped backends ignore the filter: both Qdrant clients, Elasticsearch, OpenSearch, both Milvus clients, openGauss, Oracle 23ai, Pinecone, S3 Vectors and Weaviate. Chroma, pgvector, MariaDB and Valkey apply it and were never affected.
• The caller needs a model that can call tools, with the knowledge built-in tools left enabled, which is the default, and with no knowledge attached to the model itself. No elevated role or permission is required.
• At least one knowledge base must exist that the caller cannot otherwise read.

Impact

A user receives the identifier, name and description of knowledge bases that were never shared with them, and chooses how many results to ask for, so the set can be enumerated by varying the query. The affected collection stores one entry per knowledge base whose text is its name and description, so where those values are themselves sensitive, for example when they name a customer, a project or an investigation, that disclosure is the loss.

The exposure is confined to that metadata. Document text lives in separate per-knowledge-base collections reached by a different call that is scoped by collection rather than by this filter, so stored documents are not returned by this path, and no write access is gained. Because the default backend is unaffected, the population at risk is operators who deliberately moved to an external vector store, which in practice means larger deployments.

Fix

Fixed in 0.11.1 by 1d6d4e6e6. Every affected backend now applies the caller-supplied filter in its search method, combined with the collection or tenant scoping that method already performed. Where a backend's filter builder could express only single-value equality it was extended to express set membership, since that is the form the knowledge tool sends, and a filter using any other operator is now rejected rather than dropped. Upgrading is sufficient and no configuration change is required. Deployments on Chroma, pgvector, MariaDB or Valkey were never affected and need no action.

Root cause

• The search method of each affected vector client, which declares a filter parameter and never references it.
• The built-in knowledge search tool, which relies on that filter as its only access check.
• Present from 0.7.0, the release that introduced the tool, through 0.11.0.

Each client exposes a search method and a query method that appear interchangeable from the calling side and differ in whether the caller's filter survives. Search built its request with collection or tenant scoping only, so it was correctly scoped to the collection and entirely unscoped within it. The knowledge tool resolves the caller's readable knowledge bases correctly and passes them down, then reads the results without rechecking them, on the reasonable assumption that a filter handed to a vector store is applied. Because the access decision was delegated wholly to a parameter that most implementations discarded, the caller had no way to observe that it received more than it asked for.

That the same omission repeated across most backends points at the shared interface rather than at any one client: the base class defines the…