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Not in CISA KEV
HIGH severity

Cross site scripting (XSS) in JupyterHub via Self-XSS leveraged by Cookie TossingGHSA-7r3h-4ph8-w38g

HIGHFix: jupyterhub/jupyterhub@e2798a0

GHSA-7r3h-4ph8-w38g is a high-severity (CVSS 8.1) Cross-site Scripting (XSS) vulnerability in jupyterhub. A fix is available for jupyterhub — see the affected versions and patch details below.

Also known asBIT-jupyterhub-2024-28233CVE-2024-28233PYSEC-2026-1480
Published
Updated
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed
Exploitation data as of Nov 7, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

  • A successful exploit gives an attacker total control of the affected component, not partial access.
  • 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 GHSA-7r3h-4ph8-w38g.

EPSS Exploitation Probability

via FIRST.org ↗
0.3%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs26th percentile — riskier than 26% of all scored CVEsHighest risk
0.00%0.28%0.55%0.83%0.1%0.3%May 26Sep 26Nov 26

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

How urgent is this, really

Where this sits among everything scored

Real-World Exposure

1 pkg affected
🐍jupyterhub

Real-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

Affected configurations:

  • Single-origin JupyterHub deployments
  • JupyterHub deployments with user-controlled applications running on subdomains or peer subdomains of either the Hub or a single-user server.

By tricking a user into visiting a malicious subdomain, the attacker can achieve an XSS directly affecting the former's session. More precisely, in the context of JupyterHub, this XSS could achieve the following:

  • Full access to JupyterHub API and user's single-user server, e.g.
    • Create and exfiltrate an API Token
    • Exfiltrate all files hosted on the user's single-user server: notebooks, images, etc.
    • Install malicious extensions. They can be used as a backdoor to silently regain access to victim's session anytime.

Patches

To prevent cookie-tossing:

  • Upgrade to JupyterHub 4.1 (both hub and user environment)
  • enable per-user domains via c.JupyterHub.subdomain_host = "https://mydomain.example.org"
  • set c.JupyterHub.cookie_host_prefix_enabled = True to enable domain-locked cookies

or, if available (applies to earlier JupyterHub versions):

  • deploy jupyterhub on its own domain, not shared with any other services
  • enable per-user domains via c.JupyterHub.subdomain_host = "https://mydomain.example.org"

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIjupyterhuball versions4.1.0pip install --upgrade 'jupyterhub==4.1.0'

Affected Products

1 product · 1 configurations
Application
jupyterhubjupyter
< 4.1.0
range

Detection & mitigation playbook

Open-source dependency

  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for jupyterhub, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update jupyterhub to 4.1.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-7r3h-4ph8-w38g is resolved across your whole dependency graph.

  3. Workarounds

    Escape or sanitise the affected output on the server side rather than relying on client-side filtering, and add a Content-Security-Policy that blocks inline script execution so injected markup cannot run even if it reaches the page.

Frequently Asked Questions

### Impact Affected configurations: - Single-origin JupyterHub deployments - JupyterHub deployments with user-controlled applications running on subdomains or peer subdomains of either the Hub or a single-user server. By tricking a user into visiting a malicious subdomain, the attacker can achieve an XSS directly affecting the former's session. More precisely, in the context of JupyterHub, this XSS could achieve the following: - Full access to JupyterHub API and user's single-user server, e.g. - Create and exfiltrate an API Token - Exfiltrate all files hosted on the user's single-user
O3 Security · Impact-Aware SCA

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Cross site scripting (XSS) in JupyterHub via Self-XSS…