CVE-2026-7149 (GCVE-0-2026-7149)
Vulnerability from cvelistv5 – Published: 2026-04-27 18:45 – Updated: 2026-04-27 19:29
VLAI
EPSS
VEX
Title
dexhunter kaggle-mcp server.py prepare_kaggle_dataset path traversal
Summary
A vulnerability has been found in dexhunter kaggle-mcp up to 406127ffcb2b91b8c10e20e6c2ca787fbc1dc92d. This vulnerability affects the function prepare_kaggle_dataset of the file src/kaggle_mcp/server.py. The manipulation of the argument competition_id leads to path traversal. The attack is possible to be carried out remotely. The exploit has been disclosed to the public and may be used. This product adopts a rolling release strategy to maintain continuous delivery. Therefore, version details for affected or updated releases cannot be specified. The project was informed of the problem early through an issue report but has not responded yet.
Severity
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-04-27 19:29 UTC
CWE
- CWE-22 - Path Traversal
Assigner
References
5 references
| URL | Tags |
|---|---|
| https://vuldb.com/vuln/359748 | vdb-entrytechnical-description |
| https://vuldb.com/vuln/359748/cti | signaturepermissions-required |
| https://vuldb.com/submit/802052 | third-party-advisory |
| https://github.com/dexhunter/kaggle-mcp/issues/1 | exploitissue-tracking |
| https://github.com/dexhunter/kaggle-mcp/ | product |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| dexhunter | kaggle-mcp |
Affected:
406127ffcb2b91b8c10e20e6c2ca787fbc1dc92d
|
guessed |
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Sightings
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|---|
Nomenclature
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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.
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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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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.