GSD-2021-34552
Vulnerability from gsd - Updated: 2023-12-13 01:23Details
Pillow through 8.2.0 and PIL (aka Python Imaging Library) through 1.1.7 allow an attacker to pass controlled parameters directly into a convert function to trigger a buffer overflow in Convert.c.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2021-34552",
"description": "Pillow through 8.2.0 and PIL (aka Python Imaging Library) through 1.1.7 allow an attacker to pass controlled parameters directly into a convert function to trigger a buffer overflow in Convert.c.",
"id": "GSD-2021-34552",
"references": [
"https://www.suse.com/security/cve/CVE-2021-34552.html",
"https://access.redhat.com/errata/RHSA-2021:4149",
"https://access.redhat.com/errata/RHSA-2021:3917",
"https://ubuntu.com/security/CVE-2021-34552",
"https://advisories.mageia.org/CVE-2021-34552.html",
"https://security.archlinux.org/CVE-2021-34552"
]
},
"gsd": {
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"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
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"id": "GSD-2021-34552",
"modified": "2023-12-13T01:23:14.116628Z",
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"advisories": [
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"affected_range": "\u003e=1.0,\u003c=1.1.7||\u003e=1.2,\u003c=8.2.0",
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"cwe_ids": [
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"CWE-937"
],
"date": "2023-01-31",
"description": "Pillow and PIL (aka Python Imaging Library) allow an attacker to pass controlled parameters directly into a convert function to trigger a buffer overflow in `Convert.c.`",
"fixed_versions": [
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"identifier": "CVE-2021-34552",
"identifiers": [
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"package_slug": "pypi/Pillow",
"pubdate": "2021-07-13",
"solution": "Upgrade to version 8.3.0 or above.",
"title": "Buffer Overflow",
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"impact": {
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"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 7.5,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:L/Au:N/C:P/I:P/A:P",
"version": "2.0"
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"exploitabilityScore": 10.0,
"impactScore": 6.4,
"obtainAllPrivilege": false,
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"severity": "HIGH",
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},
"lastModifiedDate": "2023-01-31T17:28Z",
"publishedDate": "2021-07-13T17:15Z"
}
}
}
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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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