GSD-2017-14059
Vulnerability from gsd - Updated: 2023-12-13 01:21Details
In FFmpeg 3.3.3, a DoS in cine_read_header() due to lack of an EOF check might cause huge CPU and memory consumption. When a crafted CINE file, which claims a large "duration" field in the header but does not contain sufficient backing data, is provided, the image-offset parsing loop would consume huge CPU and memory resources, since there is no EOF check inside the loop.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2017-14059",
"description": "In FFmpeg 3.3.3, a DoS in cine_read_header() due to lack of an EOF check might cause huge CPU and memory consumption. When a crafted CINE file, which claims a large \"duration\" field in the header but does not contain sufficient backing data, is provided, the image-offset parsing loop would consume huge CPU and memory resources, since there is no EOF check inside the loop.",
"id": "GSD-2017-14059",
"references": [
"https://www.suse.com/security/cve/CVE-2017-14059.html",
"https://www.debian.org/security/2017/dsa-3996",
"https://advisories.mageia.org/CVE-2017-14059.html",
"https://security.archlinux.org/CVE-2017-14059"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
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],
"details": "In FFmpeg 3.3.3, a DoS in cine_read_header() due to lack of an EOF check might cause huge CPU and memory consumption. When a crafted CINE file, which claims a large \"duration\" field in the header but does not contain sufficient backing data, is provided, the image-offset parsing loop would consume huge CPU and memory resources, since there is no EOF check inside the loop.",
"id": "GSD-2017-14059",
"modified": "2023-12-13T01:21:12.668127Z",
"schema_version": "1.4.0"
}
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"vectorString": "AV:N/AC:M/Au:N/C:N/I:N/A:C",
"version": "2.0"
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"vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
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},
"lastModifiedDate": "2019-10-03T00:03Z",
"publishedDate": "2017-08-31T15:29Z"
}
}
}
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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 |
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Nomenclature
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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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