7.7

CVSS Score

4.0

-

CVSS Score

Basic Information

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CVE-2026-46477

CVE-2026-46477: Flowise: Dataset create+update mass-assignment allows cross-workspace dataset takeover

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, dataset create and update mass-assignment allows cross-workspace dataset takeover. This issue has been patched in version 3.1.2.

(GitHub Advisory)

Miggo Vulnerability Database

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CVE-2026-46477

CVE-2026-46477:

7.7

CVSS Score

4.0

-

CVSS Score

Basic Information

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Technical Details

SSVC / BOD 26-04 ↗

Exploitation NoneAutomatable NoTech Impact Total

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Package Name	Ecosystem	Vulnerable Versions	First Patched Version
flowise	npm	<= 3.1.1	3.1.2

Technical Details

Vulnerability Intelligence
Miggo AI

Root Cause Analysis

The vulnerability is a classic mass assignment issue in the FlowiseAI application, specifically within the dataset and dataset row management services. The core of the problem lies in the use of Object.assign(entity, body) in the createDataset, updateDataset, addDatasetRow, and updateDatasetRow functions located in packages/server/src/services/dataset/index.ts. This programming pattern blindly copies all properties from the user-controlled request body (body) into the database entity (entity).

An authenticated attacker could exploit this by crafting a request that includes protected properties like workspaceId or id. For instance, by sending a PUT request to update a dataset and including a different workspaceId in the JSON payload, the attacker could move the dataset to another workspace. This would expose the dataset to users of the target workspace and make it inaccessible from its original location, constituting a cross-workspace data takeover.

The patch addresses this vulnerability by replacing the unsafe Object.assign with an explicit property-by-property assignment (an allowlist approach). The fixed code only assigns values for fields that are meant to be user-modifiable (e.g., name, description), while ignoring any other malicious or unintended properties sent in the request. This ensures that critical, server-managed fields like workspaceId and id cannot be manipulated by the client, thus mitigating the mass assignment vulnerability.

Vulnerable functions

createDataset

packages/server/src/services/dataset/index.ts

The function was vulnerable to mass assignment because it used `Object.assign` to copy all properties from the request body into a new `Dataset` entity. This allowed an attacker to set protected properties like `id`, leading to potential IDOR vulnerabilities.

updateDataset

packages/server/src/services/dataset/index.ts

The function was vulnerable to mass assignment. It created a new `Dataset` object, copied the request body into it using `Object.assign`, and then merged it with the existing entity. This allowed an attacker to overwrite the `workspaceId` of an existing dataset, effectively moving it to another workspace and leading to a cross-workspace data takeover.

addDatasetRow

packages/server/src/services/dataset/index.ts

Similar to `createDataset`, this function used `Object.assign` on a new `DatasetRow` entity, making it vulnerable to mass assignment of properties from the request body. This could allow an attacker to set properties that should be server-controlled.

updateDatasetRow

packages/server/src/services/dataset/index.ts

Similar to `updateDataset`, this function was vulnerable to mass assignment when updating a `DatasetRow`. An attacker could have potentially modified properties they shouldn't have access to by including them in the request body.

Vulnerability Intelligence
Miggo AI

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WAF Protection Rules

WAF Rule

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Reasoning

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