GHSA-r4v7-6wcg-ghj5
MEDIUMFileBrowser: Missing Rate Limiting on Authentication Endpoint Enables Brute Force Attacks
Blast Radius
github.com/gtsteffaniak/filebrowserReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects Go packages — download data is not available via public APIs for these ecosystems.
Description
Summary
The /api/auth/login endpoint does not implement rate limiting, account lockout, or progressive backoff for repeated authentication failures. As a result, an attacker can perform unlimited login attempts against the endpoint. When combined with the username enumeration timing vulnerability, valid accounts can be identified and then brute-forced without restriction. The risk is further increased by a weak default password policy that only enforces a minimum length of five characters.
Details
The authentication endpoint /api/auth/login does not enforce any form of rate limiting, account lockout, or progressive backoff for repeated failed login attempts. Testing confirmed that the endpoint accepts an unlimited number of authentication attempts from the same client without delay or restriction.
This allows attackers to repeatedly attempt password guesses against valid usernames.
Secure authentication systems typically enforce request throttling, temporary account lockout, or progressive delays after repeated failed login attempts to mitigate brute-force attacks.
$ python rate-limit-probe.py
[*] Probing http://localhost/api/auth/login for rate limiting, lockout, and backoff behavior...
Attempt 10: status=401, latency=0.0411s
Attempt 20: status=401, latency=0.0411s
Attempt 30: status=401, latency=0.0402s
Attempt 40: status=401, latency=0.0420s
Attempt 50: status=401, latency=0.0403s
Attempt 60: status=401, latency=0.0423s
Attempt 70: status=401, latency=0.0474s
Attempt 80: status=401, latency=0.0417s
Attempt 90: status=401, latency=0.0407s
Attempt 100: status=401, latency=0.0407s
--- CONCRETE EVIDENCE ---
Attempts completed: 100
Total runtime: 4.17s
Average request rate: 23.98 req/sec
Unique status codes: [401]
Average time (first 5): 0.0447s
Average time (last 5): 0.0408s
Latency delta: -0.0038s
[RESULT] No HTTP 429 responses observed.
[RESULT] No progressive backoff detected: response timing remained effectively constant.
Additional Context
Password validation is implemented in backend/database/storage/bolt/user.go via checkPassword(), which only verifies that the supplied password length is greater than or equal to settings.Config.Auth.Methods.PasswordAuth.MinLength. In backend/common/settings/auth.go, the PasswordAuthConfig documents the default value of MinLength as 5. No additional complexity requirements, such as uppercase, lowercase, numeric, or special character checks, were identified in this code path.
PoC
The script below demonstrates the lack of rate limiting by performing a high volume automated authentication test. The script sends sequential login requests and monitors for HTTP 429 (Too Many Requests) status codes.
import requests
import time
import statistics
URL = "http://localhost/api/auth/login"
USERNAME = "admin"
PASSWORD = "wrong-password"
MAX_ATTEMPTS = 100
TIMEOUT = 10
latencies = []
statuses = []
print(f"[*] Probing {URL} for rate limiting, lockout, and backoff behavior...")
start_total = time.time()
for i in range(1, MAX_ATTEMPTS + 1):
start = time.perf_counter()
resp = requests.post(
URL,
params={"username": USERNAME, "recaptcha": ""},
headers={"X-Password": PASSWORD},
timeout=TIMEOUT
)
duration = time.perf_counter() - start
latencies.append(duration)
statuses.append(resp.status_code)
if resp.status_code == 429:
print(f"[!] Rate limit detected at attempt {i} (HTTP 429)")
break
if i % 10 == 0:
print(f" Attempt {i:3}: status={resp.status_code}, latency={duration:.4f}s")
end_total = time.time()
attempts_completed = len(latencies)
print("\n--- CONCRETE EVIDENCE ---")
first_five_avg = statistics.mean(latencies[:5]) if attempts_completed >= 5 else statistics.mean(latencies)
last_five_avg = statistics.mean(latencies[-5:]) if attempts_completed >= 5 else statistics.mean(latencies)
latency_delta = last_five_avg - first_five_avg
print(f"Attempts completed: {attempts_completed}")
print(f"Total runtime: {end_total - start_total:.2f}s")
print(f"Average request rate: {attempts_completed / (end_total - start_total):.2f} req/sec")
print(f"Unique status codes: {sorted(set(statuses))}")
print(f"Average time (first 5): {first_five_avg:.4f}s")
print(f"Average time (last 5): {last_five_avg:.4f}s")
print(f"Latency delta: {latency_delta:+.4f}s")
if 429 not in statuses:
print("[RESULT] No HTTP 429 responses observed.")
if abs(latency_delta) < 0.05:
print("[RESULT] No progressive backoff detected: response timing remained effectively constant.")
else:
print("[RESULT] Latency variation detected: investigate possible throttling or environmental noise.")
Impact
An attacker can perform unlimited authentication attempts against valid usernames. When combined with the username enumeration timing vulnerability, this enables targeted brute-force attacks against user accounts and increases the likelihood of credential compromise.
Please let me know if you need any additional information or clarification. I'm happy to assist with testing or validating a fix.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐹Go | github.com/gtsteffaniak/filebrowser | all versions | 0.0.0-20260522161427-fa5abc8c67f3a |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for github.com/gtsteffaniak/filebrowser. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.
Fix
Update github.com/gtsteffaniak/filebrowser to 0.0.0-20260522161427-fa5abc8c67f3a or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-r4v7-6wcg-ghj5 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 pinpoints whether GHSA-r4v7-6wcg-ghj5 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.
Tailored to GHSA-r4v7-6wcg-ghj5. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-r4v7-6wcg-ghj5 in your dependencies?
O3 detects GHSA-r4v7-6wcg-ghj5 across Go dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.