Summary

fastapi-guard detects penetration attempts by using regex patterns to scan incoming requests. However, some of the regex patterns used in detection are extremely inefficient and can cause polynomial complexity backtracks when handling specially crafted inputs.

It is not as severe as exponential complexity ReDoS, but still downgrades performance and allows DoS exploits. An attacker can trigger high cpu usage and make a service unresponsive for hours by sending a single request in size of KBs.

PoC

e.g. https://github.com/rennf93/fastapi-guard/blob/1e6c2873bfc7866adcbe5fc4da72f2d79ea552e7/guard/handlers/suspatternshandler.py#L31C79-L32C7

python payload = lambda n: '<'n+ ' 'n+ 'style=' + '"'n + ' 'n+ 'url('n # complexity: O(n^5)

print(requests.post("http://172.24.1.3:8000/", data=payload(50)).elapsed) # 0:00:03.771120 print(requests.post("http://172.24.1.3:8000/", data=payload(100)).elapsed) # 0:01:17.952637 print(requests.post("http://172.24.1.3:8000/", data=payload(200)).elapsed) # timeout (>15min)

Single-threaded uvicorn workers can not handle any other concurrent requests during the elapsed time.

Impact

Penetration detection is enabled by default. Services that use fastapi-guard middleware without explicitly setting enablepenetrationdetection=False are vulnerable to DoS.

A vulnerability in danswer-ai/danswer version 0.9.0 allows for denial of service through memory exhaustion. The issue arises from the use of a vulnerable version of the starlette package (<=0.49) via fastapi, which was patched in fastapi version 0.115.3. The vulnerability can be exploited by sending multiple requests to the /auth/saml/callback endpoint, leading to uncontrolled memory consumption and eventual denial of service.