CVE-2022-25368 (GCVE-0-2022-25368)
Vulnerability from cvelistv5 – Published: 2022-03-09 18:17 – Updated: 2024-08-03 04:36
VLAI
EPSS
VEX
Summary
Spectre BHB is a variant of Spectre-v2 in which malicious code uses the shared branch history (stored in the CPU BHB) to influence mispredicted branches in the victim's hardware context. Speculation caused by these mispredicted branches can then potentially be used to cause cache allocation, which can then be used to infer information that should be protected.
Severity
4.7 (Medium)
CWE
- n/a
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://amperecomputing.com/products/security-bul… | x_refsource_MISC |
| https://cve.mitre.org/cgi-bin/cvename.cgi?name=CV… | x_refsource_CONFIRM |
| https://developer.arm.com/support/arm-security-up… | x_refsource_MISC |
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"value": "Spectre BHB es una variante de Spectre-v2 en la que el c\u00f3digo malicioso usa el historial de bifurcaciones compartido (almacenado en el BHB de la CPU) para influir en las bifurcaciones mal predichas en el contexto de hardware de la v\u00edctima. Una especulaci\u00f3n causada por estas ramas mal predichas puede entonces ser usada potencialmente para causar la asignaci\u00f3n de la cach\u00e9, la cual puede ser usada para inferir informaci\u00f3n que debe ser protegida"
}
],
"id": "CVE-2022-25368",
"lastModified": "2026-06-17T04:33:28.103",
"metrics": {
"cvssMetricV2": [
{
"acInsufInfo": false,
"baseSeverity": "LOW",
"cvssData": {
"accessComplexity": "MEDIUM",
"accessVector": "LOCAL",
"authentication": "NONE",
"availabilityImpact": "NONE",
"baseScore": 1.9,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "NONE",
"vectorString": "AV:L/AC:M/Au:N/C:P/I:N/A:N",
"version": "2.0"
},
"exploitabilityScore": 3.4,
"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"source": "nvd@nist.gov",
"type": "Primary",
"userInteractionRequired": false
}
],
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "HIGH",
"attackVector": "LOCAL",
"availabilityImpact": "NONE",
"baseScore": 4.7,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:N",
"version": "3.1"
},
"exploitabilityScore": 1.0,
"impactScore": 3.6,
"source": "nvd@nist.gov",
"type": "Primary"
}
]
},
"published": "2022-03-10T17:47:07.880",
"references": [
{
"source": "cve@mitre.org",
"tags": [
"Vendor Advisory"
],
"url": "https://amperecomputing.com/products/security-bulletins/impact-of-spectre-bhb-on-ampere.html"
},
{
"source": "cve@mitre.org",
"tags": [
"Third Party Advisory",
"VDB Entry"
],
"url": "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-23960"
},
{
"source": "cve@mitre.org",
"tags": [
"Patch",
"Technical Description",
"Vendor Advisory"
],
"url": "https://developer.arm.com/support/arm-security-updates/speculative-processor-vulnerability/spectre-bhb"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Vendor Advisory"
],
"url": "https://amperecomputing.com/products/security-bulletins/impact-of-spectre-bhb-on-ampere.html"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Third Party Advisory",
"VDB Entry"
],
"url": "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-23960"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Patch",
"Technical Description",
"Vendor Advisory"
],
"url": "https://developer.arm.com/support/arm-security-updates/speculative-processor-vulnerability/spectre-bhb"
}
],
"sourceIdentifier": "cve@mitre.org",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "NVD-CWE-noinfo"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
}
]
}
},
"redhat_vex": {
"current_release_date": "2026-03-27T12:42:20+00:00",
"cve": "CVE-2022-25368",
"id": "CVE-2022-25368",
"initial_release_date": "2022-01-01T00:00:00+00:00",
"product_status:known_not_affected": "1",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "CVE-2022-25368",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2022/cve-2022-25368.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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