GSD-2021-29510
Vulnerability from gsd - Updated: 2023-12-13 01:23Details
Pydantic is a data validation and settings management using Python type hinting. In affected versions passing either `'infinity'`, `'inf'` or `float('inf')` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can't upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you'll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2021-29510",
"description": "Pydantic is a data validation and settings management using Python type hinting. In affected versions passing either `\u0027infinity\u0027`, `\u0027inf\u0027` or `float(\u0027inf\u0027)` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can\u0027t upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you\u0027ll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.",
"id": "GSD-2021-29510",
"references": [
"https://www.suse.com/security/cve/CVE-2021-29510.html",
"https://security.archlinux.org/CVE-2021-29510"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2021-29510"
],
"details": "Pydantic is a data validation and settings management using Python type hinting. In affected versions passing either `\u0027infinity\u0027`, `\u0027inf\u0027` or `float(\u0027inf\u0027)` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can\u0027t upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you\u0027ll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.",
"id": "GSD-2021-29510",
"modified": "2023-12-13T01:23:36.242776Z",
"schema_version": "1.4.0"
}
},
"namespaces": {
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"ID": "CVE-2021-29510",
"STATE": "PUBLIC",
"TITLE": "Use of \"infinity\" as an input to datetime and date fields causes infinite loop in pydantic"
},
"affects": {
"vendor": {
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"version": {
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"value": "Pydantic is a data validation and settings management using Python type hinting. In affected versions passing either `\u0027infinity\u0027`, `\u0027inf\u0027` or `float(\u0027inf\u0027)` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can\u0027t upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you\u0027ll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic."
}
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"impact": {
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"attackVector": "LOCAL",
"availabilityImpact": "LOW",
"baseScore": 3.3,
"baseSeverity": "LOW",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L",
"version": "3.1"
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"value": "CWE-835: Loop with Unreachable Exit Condition (\u0027Infinite Loop\u0027)"
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{
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}
]
},
"source": {
"advisory": "GHSA-5jqp-qgf6-3pvh",
"discovery": "UNKNOWN"
}
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"gitlab.com": {
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"cwe_ids": [
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],
"date": "2021-05-25",
"description": "By passing either `\u0027infinity\u0027`, `\u0027inf\u0027` or `float(\u0027inf\u0027)` (or their negatives) to `datetime` or `date` fields causes validation to run forever with % CPU usage (on one CPU).",
"fixed_versions": [
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"1.7.4",
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],
"identifier": "CVE-2021-29510",
"identifiers": [
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"package_slug": "pypi/pydantic",
"pubdate": "2021-05-13",
"solution": "Upgrade to versions 1.6.2, 1.7.4, 1.8.2 or above.",
"title": "Loop with Unreachable Exit Condition (Infinite Loop)",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2021-29510"
],
"uuid": "b6771a04-bd6e-4353-85c8-627792399152"
}
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"impact": {
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"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
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"integrityImpact": "NONE",
"vectorString": "AV:N/AC:L/Au:N/C:N/I:N/A:P",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 2.9,
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"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": false
},
"baseMetricV3": {
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"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
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"exploitabilityScore": 3.9,
"impactScore": 3.6
}
},
"lastModifiedDate": "2021-05-25T14:21Z",
"publishedDate": "2021-05-13T19:15Z"
}
}
}
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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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