PYSEC-2023-277
Vulnerability from pysec - Published: 2023-12-11 19:15 - Updated: 2024-11-21 14:22
VLAI
Details
MindsDB connects artificial intelligence models to real time data. Versions prior to 23.11.4.1 contain a server-side request forgery vulnerability in file.py. This can lead to limited information disclosure. Users should use MindsDB's staging branch or v23.11.4.1, which contain a fix for the issue.
Severity
5.3 (Medium)
Impacted products
| Name | purl | mindsdb | pkg:pypi/mindsdb |
|---|
Aliases
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "mindsdb",
"purl": "pkg:pypi/mindsdb"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "8d13c9c28ebcf3b36509eb679378004d4648d8fe"
}
],
"repo": "https://github.com/mindsdb/mindsdb",
"type": "GIT"
},
{
"events": [
{
"introduced": "0"
},
{
"fixed": "23.11.4.1"
}
],
"type": "ECOSYSTEM"
}
],
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]
}
],
"aliases": [
"CVE-2023-49795",
"GHSA-34mr-6q8x-g9r6"
],
"details": "MindsDB connects artificial intelligence models to real time data. Versions prior to 23.11.4.1 contain a server-side request forgery vulnerability in `file.py`. This can lead to limited information disclosure. Users should use MindsDB\u0027s `staging` branch or v23.11.4.1, which contain a fix for the issue.\n",
"id": "PYSEC-2023-277",
"modified": "2024-11-21T14:22:54.391272+00:00",
"published": "2023-12-11T19:15:00+00:00",
"references": [
{
"type": "ADVISORY",
"url": "https://github.com/mindsdb/mindsdb/security/advisories/GHSA-34mr-6q8x-g9r6"
},
{
"type": "FIX",
"url": "https://github.com/mindsdb/mindsdb/commit/8d13c9c28ebcf3b36509eb679378004d4648d8fe"
}
],
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N",
"type": "CVSS_V3"
}
]
}
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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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