FKIE_CVE-2025-10348
Vulnerability from fkie_nvd - Published: 2025-10-30 13:15 - Updated: 2026-10-08 10:10
Severity
Summary
URVE Smart Office is vulnerable to Stored XSS in report problem functionality. An attacker with a low-privileged account can upload an SVG file containing a malicious payload, which will be executed when a victim visits the URL of the uploaded resource. The resource is available to anyone without any form of authentication.
This issue was fixed in version 1.1.24.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"defaultStatus": "unaffected",
"product": "URVE Smart Office",
"vendor": "Eveo",
"versions": [
{
"lessThan": "1.1.24",
"status": "affected",
"version": "0",
"versionType": "semver"
}
]
}
],
"source": "cvd@cert.pl"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "URVE Smart Office is vulnerable to Stored XSS in report problem functionality. An attacker with a low-privileged account can upload an SVG file containing a malicious payload, which will be executed when a victim visits the URL of the uploaded resource. The resource is available to anyone without any form of authentication.\n\nThis issue was fixed in version 1.1.24."
},
{
"lang": "es",
"value": "URVE Smart Office es vulnerable a XSS Almacenado en la funcionalidad de reportar problemas. Un atacante con una cuenta de bajos privilegios puede subir un archivo SVG que contenga una carga \u00fatil maliciosa, la cual se ejecutar\u00e1 cuando una v\u00edctima visite la URL del recurso subido. El recurso est\u00e1 disponible para cualquiera sin ninguna forma de autenticaci\u00f3n.\n\nEste problema fue solucionado en la versi\u00f3n 1.1.24."
}
],
"id": "CVE-2025-10348",
"lastModified": "2026-10-08T10:10:00.227",
"metrics": {
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "NONE",
"attackVector": "NETWORK",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 5.1,
"baseSeverity": "MEDIUM",
"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": "LOW",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "LOW",
"subIntegrityImpact": "LOW",
"userInteraction": "PASSIVE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:P/VC:N/VI:N/VA:N/SC:L/SI:L/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": "NONE",
"vulnConfidentialityImpact": "NONE",
"vulnIntegrityImpact": "NONE",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "cvd@cert.pl",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2025-10348",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-10-30T14:26:26.093717Z",
"version": "2.0.3"
}
}
]
},
"published": "2025-10-30T13:15:32.500",
"references": [
{
"source": "cvd@cert.pl",
"url": "https://cert.pl/posts/2025/10/CVE-2025-10348"
},
{
"source": "cvd@cert.pl",
"url": "https://smartoffice.expert/"
}
],
"sourceIdentifier": "cvd@cert.pl",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-79"
}
],
"source": "cvd@cert.pl",
"type": "Secondary"
}
]
}
Loading…
Loading…
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.
Loading…
Loading…
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.
Loading…
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.
Loading…