Vulnerability-Lookup

OPENSUSE-SU-2026:10427-1

Vulnerability from csaf_opensuse - Published: 2026-03-25 00:00 - Updated: 2026-09-17 16:58

Summary

jupyter-matplotlib-0.11.7-17.1 on GA media

Severity

Moderate

Notes

Title of the patch: jupyter-matplotlib-0.11.7-17.1 on GA media

Description of the patch: These are all security issues fixed in the jupyter-matplotlib-0.11.7-17.1 package on the GA media of openSUSE Tumbleweed.

Patchnames: openSUSE-Tumbleweed-2026-10427

CVE-2026-27601

5.3 (Medium)


                
                  CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L

Affected products

Recommended 16 products

Product	Version	Remediation
Unresolved product id: openSUSE Tumbleweed:jupyter-matplotlib-0:0.11.7-17.1.aarch64	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:jupyter-matplotlib-0:0.11.7-17.1.ppc64le	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:jupyter-matplotlib-0:0.11.7-17.1.s390x	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:jupyter-matplotlib-0:0.11.7-17.1.x86_64	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:jupyter-matplotlib-jupyterlab-0:0.11.7-17.1.aarch64	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:jupyter-matplotlib-jupyterlab-0:0.11.7-17.1.ppc64le	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:jupyter-matplotlib-jupyterlab-0:0.11.7-17.1.s390x	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:jupyter-matplotlib-jupyterlab-0:0.11.7-17.1.x86_64	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python311-ipympl-0:0.9.7-17.1.aarch64	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python311-ipympl-0:0.9.7-17.1.ppc64le	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python311-ipympl-0:0.9.7-17.1.s390x	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python311-ipympl-0:0.9.7-17.1.x86_64	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python313-ipympl-0:0.9.7-17.1.aarch64	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python313-ipympl-0:0.9.7-17.1.ppc64le	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python313-ipympl-0:0.9.7-17.1.s390x	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python313-ipympl-0:0.9.7-17.1.x86_64	—	Vendor Fix

Threats

Impact moderate

References

5 references

URL	Category
https://www.suse.com/support/security/rating/	external
https://ftp.suse.com/pub/projects/security/csaf/o…	self
https://www.suse.com/security/cve/CVE-2026-27601/	self
https://www.suse.com/security/cve/CVE-2026-27601	external
https://bugzilla.suse.com/1259157	external

JSON

To clipboard

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    }
  ]
}

CVE-2026-27601 (GCVE-0-2026-27601)

Vulnerability from cvelistv5 – Published: 2026-03-03 22:38 – Updated: 2026-03-04 16:44

Title

Underscore.js has unlimited recursion in _.flatten and _.isEqual, potential for DoS attack

Summary

Underscore.js is a utility-belt library for JavaScript. Prior to 1.13.8, the _.flatten and _.isEqual functions use recursion without a depth limit. Under very specific conditions, detailed below, an attacker could exploit this in a Denial of Service (DoS) attack by triggering a stack overflow. Untrusted input must be used to create a recursive datastructure, for example using JSON.parse, with no enforced depth limit. The datastructure thus created must be passed to _.flatten or _.isEqual. In the case of _.flatten, the vulnerability can only be exploited if it is possible for a remote client to prepare a datastructure that consists of arrays at all levels AND if no finite depth limit is passed as the second argument to _.flatten. In the case of _.isEqual, the vulnerability can only be exploited if there exists a code path in which two distinct datastructures that were submitted by the same remote client are compared using _.isEqual. For example, if a client submits data that are stored in a database, and the same client can later submit another datastructure that is then compared to the data that were saved in the database previously, OR if a client submits a single request, but its data are parsed twice, creating two non-identical but equivalent datastructures that are then compared. Exceptions originating from the call to _.flatten or _.isEqual, as a result of a stack overflow, are not being caught. This vulnerability is fixed in 1.13.8.

Severity

8.2 (High)


                        
                          CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

SSVC

Exploitation: none Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-03-04 16:44 UTC

CWE

CWE-770 - Allocation of Resources Without Limits or Throttling

Assigner

GitHub_M mitre root

References

3 references

URL	Tags
https://github.com/jashkenas/underscore/security/…	x_refsource_CONFIRM
https://github.com/jashkenas/underscore/commit/41…	x_refsource_MISC
https://github.com/jashkenas/underscore/commit/a6…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
jashkenas	underscore	Affected: < 1.13.8

Show details on NVD website

JSON

To clipboard

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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.

Detection rules are retrieved from Rulezet.

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.

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.