GSD-2017-5840
Vulnerability from gsd - Updated: 2023-12-13 01:21Details
The qtdemux_parse_samples function in gst/isomp4/qtdemux.c in gst-plugins-good in GStreamer before 1.10.3 allows remote attackers to cause a denial of service (out-of-bounds heap read) via vectors involving the current stts index.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2017-5840",
"description": "The qtdemux_parse_samples function in gst/isomp4/qtdemux.c in gst-plugins-good in GStreamer before 1.10.3 allows remote attackers to cause a denial of service (out-of-bounds heap read) via vectors involving the current stts index.",
"id": "GSD-2017-5840",
"references": [
"https://www.suse.com/security/cve/CVE-2017-5840.html",
"https://www.debian.org/security/2017/dsa-3820",
"https://access.redhat.com/errata/RHSA-2017:2060",
"https://ubuntu.com/security/CVE-2017-5840",
"https://advisories.mageia.org/CVE-2017-5840.html",
"https://security.archlinux.org/CVE-2017-5840",
"https://linux.oracle.com/cve/CVE-2017-5840.html"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2017-5840"
],
"details": "The qtdemux_parse_samples function in gst/isomp4/qtdemux.c in gst-plugins-good in GStreamer before 1.10.3 allows remote attackers to cause a denial of service (out-of-bounds heap read) via vectors involving the current stts index.",
"id": "GSD-2017-5840",
"modified": "2023-12-13T01:21:14.115194Z",
"schema_version": "1.4.0"
}
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},
"impact": {
"baseMetricV2": {
"cvssV2": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 5.0,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:L/Au:N/C:N/I:N/A:P",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": false
},
"baseMetricV3": {
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"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.0"
},
"exploitabilityScore": 3.9,
"impactScore": 3.6
}
},
"lastModifiedDate": "2020-05-30T18:15Z",
"publishedDate": "2017-02-09T15:59Z"
}
}
}
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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
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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
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