FKIE_CVE-2025-62802
Vulnerability from fkie_nvd - Published: 2025-10-28 22:15 - Updated: 2026-10-08 11:10
Severity
4.3 (Medium) - CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:L/A:N
4.3 (Medium) - CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:L/A:N
4.3 (Medium) - CVSS:3.1/
Summary
DNN (formerly DotNetNuke) is an open-source web content management platform (CMS) in the Microsoft ecosystem. Prior to 10.1.1, the out-of-box experience for HTML editing allows unauthenticated users to upload files. This opens a potential vector to other security issues and is not needed on most implementations. This vulnerability is fixed in 10.1.1.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| dnnsoftware | dotnetnuke | * |
{
"affected": [
{
"affectedData": [
{
"product": "Dnn.Platform",
"vendor": "dnnsoftware",
"versions": [
{
"status": "affected",
"version": "\u003c 10.1.1"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:dnnsoftware:dotnetnuke:*:*:*:*:*:*:*:*",
"matchCriteriaId": "AADA05D8-5532-4750-85C9-7B6F25E3BFD7",
"versionEndExcluding": "10.1.1",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "DNN (formerly DotNetNuke) is an open-source web content management platform (CMS) in the Microsoft ecosystem. Prior to 10.1.1, the out-of-box experience for HTML editing allows unauthenticated users to upload files. This opens a potential vector to other security issues and is not needed on most implementations. This vulnerability is fixed in 10.1.1."
},
{
"lang": "es",
"value": "DNN (anteriormente DotNetNuke) es una plataforma de gesti\u00f3n de contenido web de c\u00f3digo abierto (CMS) en el ecosistema de Microsoft. Antes de la versi\u00f3n 10.1.1, la experiencia predeterminada para la edici\u00f3n de HTML permite a los usuarios no autenticados subir archivos. Esto abre un vector potencial a otros problemas de seguridad y no es necesario en la mayor\u00eda de las implementaciones. Esta vulnerabilidad est\u00e1 corregida en la versi\u00f3n 10.1.1."
}
],
"id": "CVE-2025-62802",
"lastModified": "2026-10-08T11:10:00.250",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 4.3,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:L/A:N",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 1.4,
"source": "security-advisories@github.com",
"type": "Secondary"
},
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 4.3,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:L/A:N",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 1.4,
"source": "nvd@nist.gov",
"type": "Primary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2025-62802",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-10-29T14:53:44.556605Z",
"version": "2.0.3"
}
}
]
},
"published": "2025-10-28T22:15:38.087",
"references": [
{
"source": "security-advisories@github.com",
"tags": [
"Vendor Advisory"
],
"url": "https://github.com/dnnsoftware/Dnn.Platform/security/advisories/GHSA-2374-6cvw-qmx6"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Analyzed",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-434"
},
{
"lang": "en",
"value": "CWE-1188"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
}
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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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