FKIE_CVE-2026-102704
Vulnerability from fkie_nvd - Published: 2026-11-04 11:17 - Updated: 2026-11-04 19:17
Severity
Summary
[This CNA information record relates to multiple CVEs; the
text explains which aspects/vulnerabilities correspond to which CVE.]
A common access pattern is a batch of Grant Copy operations acting on
adjacent address ranges in the same source or destination page. For
performance reasons, Xen caches details internally to reuse already
validated data. The conditions on when to re-validate the internal data
were not correct in some cases:
- Frame numbers and grant references could wrongly be mixed up. This
is CVE-2026-102703.
- Copying by frame number (rather than grant reference) is permitted
only when operating on the caller's own memory. The check to enforce
this restriction was misplaced. This is CVE-2026-102704.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"defaultStatus": "unknown",
"product": "Xen",
"vendor": "Xen",
"versions": [
{
"status": "unknown",
"version": "consult Xen advisory XSA-523"
}
]
}
],
"source": "security@xen.org"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "[This CNA information record relates to multiple CVEs; the\ntext explains which aspects/vulnerabilities correspond to which CVE.]\n\nA common access pattern is a batch of Grant Copy operations acting on\nadjacent address ranges in the same source or destination page. For\nperformance reasons, Xen caches details internally to reuse already\nvalidated data. The conditions on when to re-validate the internal data\nwere not correct in some cases:\n\n - Frame numbers and grant references could wrongly be mixed up. This\n is CVE-2026-102703.\n\n - Copying by frame number (rather than grant reference) is permitted\n only when operating on the caller\u0027s own memory. The check to enforce\n this restriction was misplaced. This is CVE-2026-102704."
}
],
"id": "CVE-2026-102704",
"lastModified": "2026-11-04T19:17:17.937",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "NONE",
"baseScore": 4.4,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "LOW",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:N",
"version": "3.1"
},
"exploitabilityScore": 1.8,
"impactScore": 2.5,
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-102704",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-11-04T18:26:11.558066Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-11-04T11:17:07.303",
"references": [
{
"source": "security@xen.org",
"url": "https://xenbits.xenproject.org/xsa/advisory-523.html"
}
],
"sourceIdentifier": "security@xen.org",
"vulnStatus": "Received",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-693"
}
],
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"type": "Secondary"
}
]
}
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Sightings
| Author | Source | Type | Date | Other |
|---|
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
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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.
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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.