FKIE_CVE-2025-7742
Vulnerability from fkie_nvd - Published: 2025-07-25 00:15 - Updated: 2026-06-17 10:05
Severity
Summary
An authentication vulnerability exists in the LG Innotek camera model LNV5110R firmware that allows a malicious actor to upload an HTTP POST request to the devices non-volatile storage. This action may result in remote code execution that allows an attacker to run arbitrary commands on the target device at the administrator privilege level.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"defaultStatus": "affected",
"product": "Camera Model LNV5110R",
"vendor": "LG Innotek",
"versions": [
{
"status": "affected",
"version": "All",
"versionType": "custom"
}
]
}
],
"source": "product.security@lge.com"
}
],
"cveTags": [
{
"sourceIdentifier": "product.security@lge.com",
"tags": [
"unsupported-when-assigned"
]
}
],
"descriptions": [
{
"lang": "en",
"value": "An authentication vulnerability exists in the LG Innotek camera model LNV5110R firmware that allows a malicious actor to upload an HTTP POST request to the devices non-volatile storage. This action may result in remote code execution that allows an attacker to run arbitrary commands on the target device at the administrator privilege level."
},
{
"lang": "es",
"value": "Existe una vulnerabilidad de autenticaci\u00f3n en el firmware de la c\u00e1mara LG Innotek, modelo LNV5110R, que permite a un atacante cargar una solicitud HTTP POST al almacenamiento no vol\u00e1til del dispositivo. Esta acci\u00f3n puede provocar la ejecuci\u00f3n remota de c\u00f3digo, lo que permite a un atacante ejecutar comandos arbitrarios en el dispositivo objetivo con privilegios de administrador."
}
],
"id": "CVE-2025-7742",
"lastModified": "2026-06-17T10:05:34.013",
"metrics": {
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "HIGH",
"attackRequirements": "NONE",
"attackVector": "NETWORK",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 8.3,
"baseSeverity": "HIGH",
"confidentialityRequirement": "NOT_DEFINED",
"exploitMaturity": "NOT_DEFINED",
"integrityRequirement": "NOT_DEFINED",
"modifiedAttackComplexity": "NOT_DEFINED",
"modifiedAttackRequirements": "NOT_DEFINED",
"modifiedAttackVector": "NOT_DEFINED",
"modifiedPrivilegesRequired": "NOT_DEFINED",
"modifiedSubAvailabilityImpact": "NOT_DEFINED",
"modifiedSubConfidentialityImpact": "NOT_DEFINED",
"modifiedSubIntegrityImpact": "NOT_DEFINED",
"modifiedUserInteraction": "NOT_DEFINED",
"modifiedVulnAvailabilityImpact": "NOT_DEFINED",
"modifiedVulnConfidentialityImpact": "NOT_DEFINED",
"modifiedVulnIntegrityImpact": "NOT_DEFINED",
"privilegesRequired": "NONE",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "NONE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:N/VC:H/VI:L/VA:L/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"version": "4.0",
"vulnAvailabilityImpact": "LOW",
"vulnConfidentialityImpact": "HIGH",
"vulnIntegrityImpact": "LOW",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "product.security@lge.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2025-7742",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-07-25T17:32:41.623866Z",
"version": "2.0.3"
}
}
]
},
"published": "2025-07-25T00:15:24.960",
"references": [
{
"source": "product.security@lge.com",
"url": "https://www.cisa.gov/news-events/ics-advisories/icsa-25-205-04"
}
],
"sourceIdentifier": "product.security@lge.com",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-288"
}
],
"source": "product.security@lge.com",
"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
model, served locally by ML-Gateway.
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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
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