CVE-2026-4527 (GCVE-0-2026-4527)
Vulnerability from cvelistv5 – Published: 2026-05-14 05:34 – Updated: 2026-05-14 13:22
VLAI
EPSS
VEX
Title
Cross-Site Request Forgery (CSRF) in GitLab
Summary
GitLab has remediated an issue in GitLab CE/EE affecting all versions from 11.10 before 18.9.7, 18.10 before 18.10.6, and 18.11 before 18.11.3 that could have allowed an unauthenticated user to create unauthorized Jira subscriptions for a targeted user's namespace via a specially crafted link due to missing CSRF protection.
Severity
6.5 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-05-14 13:22 UTC
CWE
- CWE-352 - Cross-Site Request Forgery (CSRF)
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://gitlab.com/gitlab-org/gitlab/-/work_items… | |
| https://hackerone.com/reports/3590487 | technical-descriptionexploitpermissions-required |
| https://about.gitlab.com/releases/2026/05/13/patc… |
Impacted products
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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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