CVE-2026-30845 (GCVE-0-2026-30845)
Vulnerability from cvelistv5 – Published: 2026-03-06 19:34 – Updated: 2026-03-09 20:34
VLAI
EPSS
VEX
Title
Wekan Exposes Sensitive Data through Lack of Field Filtering During Board Publication
Summary
Wekan is an open source kanban tool built with Meteor. In versions 8.31.0 through 8.33, the board composite publication in Wekan publishes all integration data for a board without any field filtering, exposing sensitive fields including webhook URLs and authentication tokens to any subscriber. Since board publications are accessible to all board members regardless of their role (including read-only and comment-only users), and even to unauthenticated DDP clients for public boards, any user who can access a board can retrieve its webhook credentials. This token leak allows attackers to make unauthenticated requests to the exposed webhooks, potentially triggering unauthorized actions in connected external services. This issue has been fixed in version 8.34.
Severity
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-03-09 20:26 UTC
CWE
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://securitylab.github.com/advisories/GHSL-20… | x_refsource_CONFIRM |
| https://github.com/wekan/wekan/commit/8c00adc6b86… | x_refsource_MISC |
| https://github.com/wekan/wekan/releases/tag/v8.34 | x_refsource_MISC |
Impacted products
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Sightings
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|---|
Nomenclature
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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
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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.
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.