GSD-2020-11538
Vulnerability from gsd - Updated: 2023-12-13 01:22Details
In libImaging/SgiRleDecode.c in Pillow through 7.0.0, a number of out-of-bounds reads exist in the parsing of SGI image files, a different issue than CVE-2020-5311.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2020-11538",
"description": "In libImaging/SgiRleDecode.c in Pillow through 7.0.0, a number of out-of-bounds reads exist in the parsing of SGI image files, a different issue than CVE-2020-5311.",
"id": "GSD-2020-11538",
"references": [
"https://www.suse.com/security/cve/CVE-2020-11538.html",
"https://access.redhat.com/errata/RHSA-2021:0420",
"https://access.redhat.com/errata/RHSA-2020:3302",
"https://access.redhat.com/errata/RHSA-2020:3299",
"https://access.redhat.com/errata/RHSA-2020:3185",
"https://ubuntu.com/security/CVE-2020-11538",
"https://advisories.mageia.org/CVE-2020-11538.html",
"https://linux.oracle.com/cve/CVE-2020-11538.html"
]
},
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"remediation": "unknown",
"reportConfidence": "confirmed",
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"id": "GSD-2020-11538",
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"cwe_ids": [
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"CWE-125",
"CWE-937"
],
"date": "2020-07-27",
"description": "In `libImaging/SgiRleDecode.c` in Pillow, a number of out-of-bounds reads exist in the parsing of SGI image files, a different issue than CVE-2020-5311.",
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"package_slug": "pypi/Pillow",
"pubdate": "2020-06-25",
"solution": "Upgrade to version 7.1.0 or above.",
"title": "Out-of-bounds Read",
"urls": [
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"lastModifiedDate": "2023-02-27T18:01Z",
"publishedDate": "2020-06-25T19:15Z"
}
}
}
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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
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- Confirmed: The vulnerability has been validated from an analyst's perspective.
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- 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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