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Not in CISA KEV
HIGH severity

GHSA-q874-g24w-4q9g jupyter-server

HIGHFix: jupyter-server/jupyter_server@3485007

GHSA-q874-g24w-4q9g is a high-severity (CVSS 7.1) Information Exposure vulnerability in jupyter-server. A fix is available for jupyter-server — see the affected versions and patch details below.

Jupyter server Token bruteforcing

Also known asCVE-2022-29241PYSEC-2022-211
Published
Jun 16, 2022
Updated
Sep 10, 2026
Affected
2 pkgs
Patched
2 / 2
Exploits
None indexed
Exploitation data as of Sep 22, 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-q874-g24w-4q9g.

EPSS Exploitation Probability

via FIRST.org ↗
0.9%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs59th percentile — riskier than 59% of all scored CVEsHighest risk

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-q874-g24w-4q9g 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 377,636 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

2 pkgs affected
🐍jupyter-server🐍jupyter-server

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

Affects: Notebook and Lab between 6.4.0?(potentially earlier) and 6.4.11 (currently latest). Jupyter Server <=1.16.0. If I am correct about the responsible code it will affect Jupyter-Server 1.17.0 and 2.0.0a0 as well. Description: If notebook server is started with a value of root_dir that contains the starting user's home directory, then the underlying REST API can be used to leak the access token assigned at start time by guessing/brute forcing the PID of the jupyter server. While this requires an authenticated user session, this url can be used from an xss payload (as in CVE-2021-32798) or from a hooked or otherwise compromised browser to leak this access token to a malicious third party. This token can be used along with the REST API to interact with Jupyter services/notebooks such as modifying or overwriting critical files, such as .bashrc or .ssh/authorized_keys, allowing a malicious user to read potentially sensitive data and possibly gain control of the impacted system.

Affected Packages

2 total 2 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIjupyter-serverall versions1.17.1pip install --upgrade 'jupyter-server==1.17.1'
🐍PyPIjupyter-server2.0.0a0&&< 2.0.0a12.0.0a1pip install --upgrade 'jupyter-server==2.0.0a1'

Detection & mitigation playbook

Open-source dependency
  1. Detect

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

  2. Fix

    Update jupyter-server to 1.17.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-q874-g24w-4q9g is resolved across your whole dependency graph.

  3. 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.

  4. How O3 protects you

    O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-q874-g24w-4q9g can be triaged on real exposure rather than presence alone.

Tailored to GHSA-q874-g24w-4q9g. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

Affects: Notebook and Lab between 6.4.0?(potentially earlier) and 6.4.11 (currently latest). Jupyter Server <=1.16.0. If I am correct about the responsible code it will affect Jupyter-Server 1.17.0 and 2.0.0a0 as well. Description: If notebook server is started with a value of `root_dir` that contains the starting user's home directory, then the underlying REST API can be used to leak the access token assigned at start time by guessing/brute forcing the PID of the jupyter server. While this requires an authenticated user session, this url can be used from an xss payload (as in CVE-2021-32798)
O3 Security · Impact-Aware SCA

Is GHSA-q874-g24w-4q9g in your dependencies?

O3 Security finds GHSA-q874-g24w-4q9g across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.

GHSA-q874-g24w-4q9g: XSS (High 7.1) | O3 Security