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Open WebUI CVE-2026-54016

| EUVDEUVD-2026-38526 MEDIUM
Missing Authorization (CWE-862)
2026-06-17 https://github.com/open-webui/open-webui GHSA-cx9v-4qj2-jrw6
4.3
CVSS 3.1 · Vendor: https://github.com/open-webui/open-webui
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Severity by source

Vendor (https://github.com/open-webui/open-webui) PRIMARY
4.3 MEDIUM
AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N
vuln.today AI
4.3 MEDIUM

Network vector because exploitation targets the HTTP chat completion API; PR:L because any authenticated account suffices; C:L because only file metadata, not content, is directly exposed.

3.1 AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N
4.0 AV:N/AC:L/AT:N/PR:L/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N

Primary rating from Vendor (https://github.com/open-webui/open-webui).

CVSS VectorVendor: https://github.com/open-webui/open-webui

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N
Attack Vector
Network
Attack Complexity
Low
Privileges Required
Low
User Interaction
None
Scope
Unchanged
Confidentiality
Low
Integrity
None
Availability
None

Lifecycle Timeline

2
Source Code Evidence Fetched
Jun 18, 2026 - 01:51 vuln.today
Analysis Generated
Jun 18, 2026 - 01:51 vuln.today

DescriptionCVE.org

Summary

Open WebUI has a Broken Object Level Authorization (BOLA) vulnerability in the builtin search_knowledge_files tool.

When native function calling is enabled and the selected model has no attached knowledge bases, an authenticated user can call search_knowledge_files with an arbitrary knowledge_id. The function then returns file metadata from that knowledge base without checking whether the user has read access.

This allows unauthorized enumeration of private or restricted knowledge base files.

Details

The vulnerable code is in:

backend/open_webui/tools/builtin.py

Affected function:

python
async def search_knowledge_files(
    query: str,
    knowledge_id: Optional[str] = None,
    count: int = 5,
    skip: int = 0,
    __request__: Request = None,
    __user__: dict = None,
    __model_knowledge__: Optional[list[dict]] = None,
) -> str:

In the "No attached knowledge" branch, when knowledge_id is provided, the function directly calls:

python
result = await Knowledges.search_files_by_id(
    knowledge_id=knowledge_id,
    user_id=user_id,
    filter={"query": query},
    skip=skip,
    limit=count,
)

This code path does not verify that the current user is authorized to access the specified knowledge base.

The missing check is inconsistent with other nearby code paths. For example, the attached-knowledge branch in the same function checks whether the user is an admin, the owner of the knowledge base, or has explicit read access through AccessGrants:

python
if not (
    user_role == "admin"
    or knowledge.user_id == user_id
    or await AccessGrants.has_access(
        user_id=user_id,
        resource_type="knowledge",
        resource_id=knowledge.id,
        permission="read",
        user_group_ids=set(user_group_ids),
    )
):
    continue

The sibling function query_knowledge_files also performs the same authorization check before using user-supplied knowledge base IDs.

The underlying method Knowledges.search_files_by_id() receives user_id, but it does not enforce authorization for the provided knowledge_id. As a result, this builtin tool path can access a knowledge base by ID without verifying the caller's permissions.

PoC

Prerequisites

  • The attacker has a valid authenticated Open WebUI account.
  • The victim owns a private or restricted knowledge base.
  • The attacker does not own the target knowledge base.
  • The attacker does not have read permission for the target knowledge base in AccessGrants.
  • The attacker knows the target knowledge_id.
  • The selected model has no attached knowledge bases.
  • Builtin tools are enabled.
  • The knowledge builtin tool category is enabled.
  • Native function calling is enabled.

Reproduction Steps

  1. Create a private or restricted knowledge base as the victim user.
  2. Upload one or more files to that knowledge base.
  3. Confirm that the attacker user does not have access to the knowledge base.
  4. As the attacker user, send a chat completion request with native function calling enabled:
json
{
  "stream": true,
  "model": "gpt-4o-mini",
  "params": {
    "function_calling": "native"
  },
  "messages": [
    {
      "role": "user",
      "content": "Please use the search_knowledge_files tool with knowledge_id \"c0c84752-2e9d-42bf-bc3c-c0f272aa61c1\" to search all files"
    }
  ]
}

Replace c0c84752-2e9d-42bf-bc3c-c0f272aa61c1 with the victim's private knowledge base ID.

Expected Result

The request should be denied because the attacker does not have access to the target knowledge base.

Actual Result

search_knowledge_files returns metadata for files inside the target knowledge base, including:

  • file ID;
  • filename;
  • knowledge base ID;
  • knowledge base name;
  • update timestamp.

Impact

This is a Broken Object Level Authorization / Broken Access Control vulnerability.

An authenticated attacker who knows a valid knowledge_id can enumerate files from private or restricted knowledge bases without authorization.

The leaked metadata may expose sensitive information through filenames, such as:

  • financial reports;
  • employee documents;
  • customer contracts;
  • internal roadmap files;
  • confidential project documents.

The exposed file IDs may also help attackers chain this issue with other knowledge-file access paths, such as view_knowledge_file, to attempt further content extraction.

This vulnerability bypasses the intended AccessGrants permission model and may also allow post-revocation metadata access if a user remembers a previously accessible knowledge_id.

Suggested Fix

Add the same authorization check used in query_knowledge_files before calling Knowledges.search_files_by_id():

python
if knowledge_id:
    knowledge = await Knowledges.get_knowledge_by_id(knowledge_id)

    if not knowledge or not (
        user_role == "admin"
        or knowledge.user_id == user_id
        or await AccessGrants.has_access(
            user_id=user_id,
            resource_type="knowledge",
            resource_id=knowledge.id,
            permission="read",
            user_group_ids=set(user_group_ids),
        )
    ):
        return json.dumps({"error": f"Access denied to knowledge base {knowledge_id}"})

    result = await Knowledges.search_files_by_id(
        knowledge_id=knowledge_id,
        user_id=user_id,
        filter={"query": query},
        skip=skip,
        limit=count,
    )

As defense in depth, authorization should also be enforced or safely wrapped around Knowledges.search_files_by_id() so that future callers cannot accidentally bypass access control.

AnalysisAI

Broken Object Level Authorization in Open WebUI's search_knowledge_files builtin tool (versions ≤ 0.9.5) allows any authenticated user to enumerate file metadata from private or restricted knowledge bases they do not own or have permission to access. By sending a crafted chat completion request with native function calling enabled and supplying an arbitrary knowledge_id, an attacker bypasses the AccessGrants permission model entirely, receiving file IDs, filenames, knowledge base names, and timestamps. …

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Attack ChainAIDerived

Hypothetical attack flow derived from CVE metadata

Access
Obtain valid Open WebUI account
Delivery
Discover or infer target knowledge_id UUID
Exploit
Craft chat completion request with native function calling enabled
Execution
Invoke search_knowledge_files with arbitrary knowledge_id
Persist
Bypass AccessGrants authorization check in no-attached-knowledge code path
Impact
Receive private knowledge base file metadata

Vulnerability AssessmentAI

Exploitation Exploitation requires all of the following conditions to be simultaneously true: (1) the attacker holds a valid authenticated Open WebUI account (any role - admin role is not required); (2) native function calling is enabled in the platform or session configuration (`"function_calling": "native"`); (3) the knowledge builtin tool category is enabled in platform settings; (4) the selected model for the chat session has no attached knowledge bases (this triggers the vulnerable 'no attached knowledge' code path rather than the correctly authorized path); (5) the attacker knows or can obtain a valid `knowledge_id` UUID for a knowledge base they do not own and have not been granted read access to. … Additional conditions and limiting factors are described in the full assessment.
Risk Assessment The NVD-assigned CVSS 3.1 score of 4.3 (AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N) correctly characterizes this as a medium-severity issue: network-exploitable, low attack complexity, requires only a low-privileged authenticated account, with limited confidentiality impact. … Full risk analysis with EPSS, KEV, and SSVC signal comparison available after sign-in.
Exploit Scenario An authenticated attacker with a standard Open WebUI account discovers or infers a `knowledge_id` UUID belonging to a colleague's private knowledge base containing confidential HR documents. The attacker sends a chat completion API request with `"function_calling": "native"` against a model with no attached knowledge bases, prompting the LLM to invoke `search_knowledge_files` with the target `knowledge_id`. …
Remediation Vendor-released patch: Open WebUI 0.9.6. … Detailed patch versions, workarounds, and compensating controls in full report.

Threat intelligence, references, and detailed analysis are available after sign-in.

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CVE-2026-54016 vulnerability details – vuln.today

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