FKIE_CVE-2025-62376
Vulnerability from fkie_nvd - Published: 2025-10-14 22:15 - Updated: 2026-10-08 12:10
Severity
Summary
pwn.college DOJO is an education platform for learning cybersecurity. Prior to commit 467db0b9ea0d9a929dc89b41f6eb59f7cfc68bef, the /workspace endpoint contains an improper authentication vulnerability that allows an attacker to access any active Windows VM without proper authorization. The vulnerability occurs in the view_desktop function where the user is retrieved via a URL parameter without verifying that the requester has administrative privileges. An attacker can supply any user ID and arbitrary password in the request parameters to impersonate another user. When requesting a Windows desktop service, the function does not validate the supplied password before generating access credentials, allowing the attacker to obtain an iframe source URL that grants full access to the target user's Windows VM. This impacts all users with active Windows VMs, as an attacker can access and modify data on the Windows machine and in the home directory of the associated Linux machine via the Z: drive. This issue has been patched in commit 467db0b9ea0d9a929dc89b41f6eb59f7cfc68bef. No known workarounds exist.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"product": "dojo",
"vendor": "pwncollege",
"versions": [
{
"status": "affected",
"version": "\u003c 467db0b9ea0d9a929dc89b41f6eb59f7cfc68bef"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "pwn.college DOJO is an education platform for learning cybersecurity. Prior to commit 467db0b9ea0d9a929dc89b41f6eb59f7cfc68bef, the /workspace endpoint contains an improper authentication vulnerability that allows an attacker to access any active Windows VM without proper authorization. The vulnerability occurs in the view_desktop function where the user is retrieved via a URL parameter without verifying that the requester has administrative privileges. An attacker can supply any user ID and arbitrary password in the request parameters to impersonate another user. When requesting a Windows desktop service, the function does not validate the supplied password before generating access credentials, allowing the attacker to obtain an iframe source URL that grants full access to the target user\u0027s Windows VM. This impacts all users with active Windows VMs, as an attacker can access and modify data on the Windows machine and in the home directory of the associated Linux machine via the Z: drive. This issue has been patched in commit 467db0b9ea0d9a929dc89b41f6eb59f7cfc68bef. No known workarounds exist."
},
{
"lang": "es",
"value": "pwn.college DOJO es una plataforma educativa para aprender ciberseguridad. Antes del commit 467db0b9ea0d9a929dc89b41f6eb59f7cfc68bef, el endpoint /workspace contiene una vulnerabilidad de autenticaci\u00f3n impropia que permite a un atacante acceder a cualquier VM de Windows activa sin la autorizaci\u00f3n adecuada. La vulnerabilidad ocurre en la funci\u00f3n view_desktop donde el usuario se recupera a trav\u00e9s de un par\u00e1metro de URL sin verificar que el solicitante tenga privilegios administrativos. Un atacante puede proporcionar cualquier ID de usuario y contrase\u00f1a arbitraria en los par\u00e1metros de la solicitud para suplantar a otro usuario. Al solicitar un servicio de escritorio de Windows, la funci\u00f3n no valida la contrase\u00f1a proporcionada antes de generar credenciales de acceso, permitiendo al atacante obtener una URL de origen de iframe que otorga acceso completo a la VM de Windows del usuario objetivo. Esto afecta a todos los usuarios con VMs de Windows activas, ya que un atacante puede acceder y modificar datos en la m\u00e1quina Windows y en el directorio de inicio de la m\u00e1quina Linux asociada a trav\u00e9s de la unidad Z:. Este problema ha sido parcheado en el commit 467db0b9ea0d9a929dc89b41f6eb59f7cfc68bef. No existen soluciones alternativas conocidas."
}
],
"id": "CVE-2025-62376",
"lastModified": "2026-10-08T12:10:00.217",
"metrics": {
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "PRESENT",
"attackVector": "NETWORK",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 9.5,
"baseSeverity": "CRITICAL",
"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": "LOW",
"subConfidentialityImpact": "HIGH",
"subIntegrityImpact": "HIGH",
"userInteraction": "NONE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:H/VI:H/VA:L/SC:H/SI:H/SA:L/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": "HIGH",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "security-advisories@github.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2025-62376",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "no"
},
{
"technicalImpact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-10-15T20:11:33.542458Z",
"version": "2.0.3"
}
}
]
},
"published": "2025-10-14T22:15:38.670",
"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/pwncollege/dojo/commit/467db0b9ea0d9a929dc89b41f6eb59f7cfc68bef"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/pwncollege/dojo/security/advisories/GHSA-344w-77p7-gx2c"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-287"
}
],
"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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