FKIE_CVE-2017-15289
Vulnerability from fkie_nvd - Published: 2017-10-16 18:29 - Updated: 2026-06-17 01:07
Severity
Summary
The mode4and5 write functions in hw/display/cirrus_vga.c in Qemu allow local OS guest privileged users to cause a denial of service (out-of-bounds write access and Qemu process crash) via vectors related to dst calculation.
References
{
"affected": [
{
"affectedData": [
{
"product": "n/a",
"vendor": "n/a",
"versions": [
{
"status": "affected",
"version": "n/a"
}
]
}
],
"source": "cve@mitre.org"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:qemu:qemu:*:*:*:*:*:*:*:*",
"matchCriteriaId": "DE828526-81EF-4807-8E73-E0FC56034D8B",
"versionEndIncluding": "2.10.2",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
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]
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],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "The mode4and5 write functions in hw/display/cirrus_vga.c in Qemu allow local OS guest privileged users to cause a denial of service (out-of-bounds write access and Qemu process crash) via vectors related to dst calculation."
},
{
"lang": "es",
"value": "Las funciones de escritura mode4and5 en hw/display/cirrus_vga.c en Qemu permiten que usuarios del sistema operativo invitados con privilegios provoquen una denegaci\u00f3n de servicio (acceso de lectura fuera de l\u00edmites y cierre inesperado del proceso Qemu) mediante vectores relacionados con el c\u00e1lculo dst."
}
],
"id": "CVE-2017-15289",
"lastModified": "2026-06-17T01:07:31.697",
"metrics": {
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"accessVector": "LOCAL",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 2.1,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
"version": "2.0"
},
"exploitabilityScore": 3.9,
"impactScore": 2.9,
"obtainAllPrivilege": false,
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"attackVector": "LOCAL",
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"baseScore": 6.0,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
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"scope": "CHANGED",
"userInteraction": "NONE",
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"published": "2017-10-16T18:29:00.623",
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"sourceIdentifier": "cve@mitre.org",
"vulnStatus": "Modified",
"weaknesses": [
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}
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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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