CVE-2017-15596 (GCVE-0-2017-15596)
Vulnerability from cvelistv5 – Published: 2017-10-18 08:00 – Updated: 2024-08-05 19:57
VLAI
EPSS
VEX
Summary
An issue was discovered in Xen 4.4.x through 4.9.x allowing ARM guest OS users to cause a denial of service (prevent physical CPU usage) because of lock mishandling upon detection of an add-to-physmap error.
Severity
6.0 (Medium)
CWE
- n/a
Assigner
References
3 references
| URL | Tags |
|---|---|
| http://www.debian.org/security/2017/dsa-3969 | vendor-advisoryx_refsource_DEBIAN |
| https://xenbits.xen.org/xsa/advisory-235.html | x_refsource_CONFIRM |
| http://www.securitytracker.com/id/1039568 | vdb-entryx_refsource_SECTRACK |
Date Public
2017-10-18 00:00
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"criteria": "cpe:2.3:o:xen:xen:4.9.0:rc9:*:*:*:*:*:*",
"matchCriteriaId": "78E4BD5E-212B-4E3A-9D46-043D71339F43",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "An issue was discovered in Xen 4.4.x through 4.9.x allowing ARM guest OS users to cause a denial of service (prevent physical CPU usage) because of lock mishandling upon detection of an add-to-physmap error."
},
{
"lang": "es",
"value": "Se ha descubierto un problema en Xen desde las versiones 4.4.x hasta las versiones 4.9.x que permite que usuarios invitados del sistema operativo ARM provoquen una denegaci\u00f3n de servicio (imposibilidad de emplear los recursos f\u00edsicos de la CPU) debido a la gesti\u00f3n incorrecta de los bloqueos al detectarse un error add-to-physmap."
}
],
"id": "CVE-2017-15596",
"lastModified": "2026-05-13T00:24:29.033",
"metrics": {
"cvssMetricV2": [
{
"acInsufInfo": false,
"baseSeverity": "MEDIUM",
"cvssData": {
"accessComplexity": "LOW",
"accessVector": "LOCAL",
"authentication": "NONE",
"availabilityImpact": "COMPLETE",
"baseScore": 4.9,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:C",
"version": "2.0"
},
"exploitabilityScore": 3.9,
"impactScore": 6.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"source": "nvd@nist.gov",
"type": "Primary",
"userInteractionRequired": false
}
],
"cvssMetricV30": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 6.0,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "HIGH",
"scope": "CHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:L/AC:L/PR:H/UI:N/S:C/C:N/I:N/A:H",
"version": "3.0"
},
"exploitabilityScore": 1.5,
"impactScore": 4.0,
"source": "nvd@nist.gov",
"type": "Primary"
}
]
},
"published": "2017-10-18T08:29:00.607",
"references": [
{
"source": "cve@mitre.org",
"url": "http://www.debian.org/security/2017/dsa-3969"
},
{
"source": "cve@mitre.org",
"tags": [
"Third Party Advisory",
"VDB Entry"
],
"url": "http://www.securitytracker.com/id/1039568"
},
{
"source": "cve@mitre.org",
"tags": [
"Mitigation",
"Patch",
"Vendor Advisory"
],
"url": "https://xenbits.xen.org/xsa/advisory-235.html"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"url": "http://www.debian.org/security/2017/dsa-3969"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Third Party Advisory",
"VDB Entry"
],
"url": "http://www.securitytracker.com/id/1039568"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Mitigation",
"Patch",
"Vendor Advisory"
],
"url": "https://xenbits.xen.org/xsa/advisory-235.html"
}
],
"sourceIdentifier": "cve@mitre.org",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-400"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
}
]
}
},
"redhat_vex": {
"aggregate_severity": "Low",
"current_release_date": "2026-05-13T03:48:04+00:00",
"cve": "CVE-2017-15596",
"id": "CVE-2017-15596",
"initial_release_date": "2017-08-23T00:00:00+00:00",
"product_status:known_not_affected": "1",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "xen: add-to-physmap error paths fail to release lock on ARM",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2017/cve-2017-15596.json",
"version": "3"
}
}
}
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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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