GSD-2023-40170
Vulnerability from gsd - Updated: 2023-12-13 01:20Details
jupyter-server is the backend for Jupyter web applications. Improper cross-site credential checks on `/files/` URLs could allow exposure of certain file contents, or accessing files when opening untrusted files via "Open image in new tab". This issue has been addressed in commit `87a49272728` which has been included in release `2.7.2`. Users are advised to upgrade. Users unable to upgrade may use the lower performance `--ContentsManager.files_handler_class=jupyter_server.files.handlers.FilesHandler`, which implements the correct checks.
Aliases
Aliases
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"alias": "CVE-2023-40170",
"id": "GSD-2023-40170"
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"remediation": "unknown",
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"id": "GSD-2023-40170",
"modified": "2023-12-13T01:20:44.070383Z",
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"scope": "CHANGED",
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"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N",
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},
"lastModifiedDate": "2023-09-15T22:15Z",
"publishedDate": "2023-08-28T21:15Z"
}
}
}
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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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