CVE-2025-2420 (GCVE-0-2025-2420)
Vulnerability from cvelistv5 – Published: 2025-03-17 22:31 – Updated: 2025-03-18 13:12
VLAI
EPSS
VEX
Title
猫宁i Morning cross-site request forgery
Summary
A vulnerability classified as problematic was found in 猫宁i Morning up to bc782730c74ff080494f145cc363a0b4f43f7d3e. Affected by this vulnerability is an unknown functionality. The manipulation leads to cross-site request forgery. The attack can be launched remotely. The exploit has been disclosed to the public and may be used. This product takes the approach of rolling releases to provide continious delivery. Therefore, version details for affected and updated releases are not available.
Severity
4.3 (Medium)
4.3 (Medium)
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-03-18 13:12 UTC
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://vuldb.com/?id.299917 | vdb-entry |
| https://vuldb.com/?ctiid.299917 | signaturepermissions-required |
| https://vuldb.com/?submit.517009 | third-party-advisory |
| https://gitee.com/morning-pro/Morning/issues/IBRVMX | exploitissue-tracking |
Impacted products
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Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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Vulnerability timeline
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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.
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.