CVE-2024-37300 is a high-severity (CVSS 8.1) CWE-863 vulnerability in oauthenticator. A fix is available for oauthenticator — see the affected versions and patch details below.
Globus `identity_provider` restriction ignored when used with `allow_all` in JupyterHub 5.0
Exploitation Status
No confirmed exploitation observed yet
- CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.
Exploitation and automatability from CISA’s SSVC triage for CVE-2024-37300.
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
CVE-2024-37300 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 378,567 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
oauthenticatorReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
Impact
JupyterHub < 5.0, when used with GlobusOAuthenticator, could be configured to allow all users from a particular institution only. The configuration for this would look like:
# Require users to be using the "foo.horse" identity provider, often an institution or university
c.GlobusAuthenticator.identity_provider = "foo.horse"
# Allow everyone who has that identity provider to log in
c.GlobusAuthenticator.allow_all = True
This worked fine prior to JupyterHub 5.0, because allow_all did not take precedence over identity_provider.
Since JupyterHub 5.0, allow_all does take precedence over identity_provider. On a hub with the same config, now all users will be allowed to login, regardless of identity_provider. identity_provider will basically be ignored.
This is a documented change in JupyterHub 5.0, but is likely to catch many users by surprise.
Patches
OAuthenticator 16.3.1 fixes the issue with JupyterHub 5.0, and does not affect previous versions.
Workarounds
Do not upgrade to JupyterHub 5.0 when using GlobusOAuthenticator in the prior configuration.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | oauthenticator | all versions | 16.3.1pip install --upgrade 'oauthenticator==16.3.1' |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for oauthenticator, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update oauthenticator to 16.3.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2024-37300 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 CVE-2024-37300 can be triaged on real exposure rather than presence alone.
Tailored to CVE-2024-37300. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is CVE-2024-37300 in your dependencies?
O3 Security finds CVE-2024-37300 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.