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EUVD-2026-361081
European Vulnerability Database identifier assigned by ENISAReserved
2026-10-02 08:30
Assigner
ENISA
Alias of
a CVE record, shown under related vulnerabilities.
This identifier carries no description, severity or references of its own:
they belong to that CVE.
{
"assigner": "ENISA",
"date_reserved": "2026-10-02T08:30:55.956353+00:00",
"id": "EUVD-2026-361081"
}
CVE-2026-44727 (GCVE-0-2026-44727)
Vulnerability from cvelistv5 – Published: 2026-06-22 19:56 – Updated: 2026-08-28 12:04
VLAI
EPSS
VEX
Title
Jupyter Server: Stored XSS in `NbconvertFileHandler` / `NbconvertPostHandler` via missing `sandbox` CSP
Summary
Jupyter Server is the backend for Jupyter web applications. Prior to 2.20, the nbconvert HTTP handlers in jupyter_server render user-authored notebook HTML under the Jupyter origin without a sandbox directive in their Content-Security-Policy. Combined with nbconvert.HTMLExporter's default non-sanitizing behavior, a notebook carrying an HTML payload in a display_data output triggers stored XSS with cookie access, full /api/* authority, and kernel RCE. This vulnerability is fixed in 2.20.
Severity
9 (Critical)
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-06-23 12:15 UTC
CWE
Assigner
References
7 references
| URL | Tags |
|---|---|
| https://github.com/jupyter-server/jupyter_server/… | x_refsource_CONFIRM |
| https://github.com/jupyter-server/jupyter_server/… | x_refsource_MISC |
| https://access.redhat.com/security/cve/CVE-2026-44727 | vdb-entryx_refsource_REDHAT |
| https://bugzilla.redhat.com/show_bug.cgi?id=2491516 | issue-trackingx_refsource_REDHAT |
| https://security.access.redhat.com/data/csaf/v2/v… | x_sadp-csaf-vex |
| https://access.redhat.com/errata/RHSA-2026:43038 | vendor-advisoryx_refsource_REDHAT |
| https://access.redhat.com/errata/RHSA-2026:60520 | vendor-advisoryx_refsource_REDHAT |
Impacted products
15 products
| Vendor | Product | Version | |
|---|---|---|---|
| jupyter-server | jupyter_server |
Affected:
< 2.20
|
|
| Red Hat | Red Hat Migration Toolkit for Applications 8.2 |
Unaffected:
1784109883 , < *
(rpm)
cpe:/a:redhat:migration_toolkit_applications:8.2::el9 |
|
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1787076778 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
|
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1787077779 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
|
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1787076481 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
|
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1787074331 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
|
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1787073913 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
|
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1787074078 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
|
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1787073929 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
|
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1787073605 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
|
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1787073546 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
|
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1787073717 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
|
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1787073713 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
|
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1787073593 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
|
| Red Hat | Red Hat OpenShift AI (RHOAI) |
cpe:/a:redhat:openshift_ai
|
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Trend slope:
-
(linear fit over daily sighting counts)
Show additional events:
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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