CVE-2025-65962 (GCVE-0-2025-65962)
Vulnerability from cvelistv5 – Published: 2025-12-08 23:15 – Updated: 2025-12-09 16:04
VLAI
EPSS
VEX
Title
Tuleap has missing CSRF protections its in tracker field dependencies
Summary
Tuleap is a free and open source suite for management of software development and collaboration. Versions of Tuleap Community Edition prior to 17.0.99.1763803709 and Tuleap Enterprise Edition versions prior to 17.0-4 and 16.13-9 are mission CSRF protections in its tracker field dependencies, allowing attackers to modify tracker fields. This issue is fixed in Tuleap Community Edition version 17.0.99.1763803709 and Tuleap Enterprise Edition versions 17.0-4 and 16.13-9.
Severity
4.6 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-12-09 14:18 UTC
CWE
- CWE-352 - Cross-Site Request Forgery (CSRF)
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://github.com/Enalean/tuleap/security/adviso… | x_refsource_CONFIRM |
| https://github.com/Enalean/tuleap/commit/26678c5b… | x_refsource_MISC |
| https://tuleap.net/plugins/git/tuleap/tuleap/stab… | x_refsource_MISC |
| https://tuleap.net/plugins/tracker/?aid=45632 | x_refsource_MISC |
Impacted products
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Sightings
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|---|
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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.
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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.
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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.