GSD-2023-51434
Vulnerability from gsd - Updated: 2023-12-19 06:01Details
Some Honor products are affected by buffer overflow vulnerability, successful exploitation could cause code execution.
Aliases
{
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2023-51434"
],
"details": "\nSome Honor products are affected by buffer overflow vulnerability, successful exploitation could cause code execution.\n\n",
"id": "GSD-2023-51434",
"modified": "2023-12-19T06:01:24.332403Z",
"schema_version": "1.4.0"
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"affects": {
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{
"product": {
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"product_name": "Magic UI",
"version": {
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{
"version_affected": "\u003c",
"version_name": "6.0",
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}
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}
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"description": {
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"value": "\nSome Honor products are affected by buffer overflow vulnerability, successful exploitation could cause code execution.\n\n"
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"impact": {
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"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 9.3,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "CHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H",
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"url": "https://www.hihonor.com/global/security/cve-2023-51434/"
}
]
},
"source": {
"discovery": "UNKNOWN"
}
},
"nvd.nist.gov": {
"cve": {
"configurations": [
{
"nodes": [
{
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{
"criteria": "cpe:2.3:o:hihonor:magic_ui:*:*:*:*:*:*:*:*",
"matchCriteriaId": "7342B2B6-C9E8-465F-A77F-98912A1CF1AF",
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"value": "\nSome Honor products are affected by buffer overflow vulnerability, successful exploitation could cause code execution.\n\n"
},
{
"lang": "es",
"value": "Algunos productos Honor se ven afectados por una vulnerabilidad de desbordamiento de b\u00fafer; una explotaci\u00f3n exitosa podr\u00eda provocar la ejecuci\u00f3n del c\u00f3digo."
}
],
"id": "CVE-2023-51434",
"lastModified": "2024-01-05T16:08:52.337",
"metrics": {
"cvssMetricV31": [
{
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"attackComplexity": "LOW",
"attackVector": "LOCAL",
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"source": "3836d913-7555-4dd0-a509-f5667fdf5fe4",
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"published": "2023-12-29T04:15:10.513",
"references": [
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"source": "3836d913-7555-4dd0-a509-f5667fdf5fe4",
"tags": [
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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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