FKIE_CVE-2025-27142
Vulnerability from fkie_nvd - Published: 2025-02-25 20:15 - Updated: 2026-06-17 09:03
Severity
Summary
LocalSend is a free, open-source app that allows users to securely share files and messages with nearby devices over their local network without needing an internet connection. Prior to version 1.17.0, due to the missing sanitization of the path in the `POST /api/localsend/v2/prepare-upload` and the `POST /api/localsend/v2/upload` endpoint, a malicious file transfer request can write files to the arbitrary location on the system, resulting in the remote command execution. A malicious file transfer request sent by nearby devices can write files into an arbitrary directory. This usually allows command execution via the startup folder on Windows or Bash-related files on Linux. If the user enables the `Quick Save` feature, it will silently write files without explicit user interaction. Version 1.17.0 fixes this issue.
References
{
"affected": [
{
"affectedData": [
{
"product": "localsend",
"vendor": "localsend",
"versions": [
{
"status": "affected",
"version": "\u003c 1.17.0"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:localsend:localsend:*:*:*:*:*:*:*:*",
"matchCriteriaId": "99B665EA-3DCE-4331-ACFE-C4A38FCF8D1B",
"versionEndExcluding": "1.17.0",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "LocalSend is a free, open-source app that allows users to securely share files and messages with nearby devices over their local network without needing an internet connection. Prior to version 1.17.0, due to the missing sanitization of the path in the `POST /api/localsend/v2/prepare-upload` and the `POST /api/localsend/v2/upload` endpoint, a malicious file transfer request can write files to the arbitrary location on the system, resulting in the remote command execution. A malicious file transfer request sent by nearby devices can write files into an arbitrary directory. This usually allows command execution via the startup folder on Windows or Bash-related files on Linux. If the user enables the `Quick Save` feature, it will silently write files without explicit user interaction. Version 1.17.0 fixes this issue."
},
{
"lang": "es",
"value": "LocalSend es una aplicaci\u00f3n gratuita de c\u00f3digo abierto que permite a los usuarios compartir archivos y mensajes de forma segura con dispositivos cercanos a trav\u00e9s de su red local sin necesidad de una conexi\u00f3n a Internet. Antes de la versi\u00f3n 1.17.0, debido a la falta de depuraci\u00f3n de la ruta en el endpoint `POST /api/localsend/v2/prepare-upload` y `POST /api/localsend/v2/upload`, una solicitud de transferencia de archivos maliciosa puede escribir archivos en una ubicaci\u00f3n arbitraria en el sistema, lo que da como resultado la ejecuci\u00f3n remota del comando. Una solicitud de transferencia de archivos maliciosa enviada por dispositivos cercanos puede escribir archivos en un directorio arbitrario. Esto generalmente permite la ejecuci\u00f3n de comandos a trav\u00e9s de la carpeta de inicio en Windows o archivos relacionados con Bash en Linux. Si el usuario habilita la funci\u00f3n `Guardado r\u00e1pido`, escribir\u00e1 archivos de forma silenciosa sin interacci\u00f3n expl\u00edcita del usuario. La versi\u00f3n 1.17.0 corrige este problema."
}
],
"id": "CVE-2025-27142",
"lastModified": "2026-06-17T09:03:05.440",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "ADJACENT_NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 5.9,
"source": "nvd@nist.gov",
"type": "Primary"
}
],
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "NONE",
"attackVector": "ADJACENT",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 6.3,
"baseSeverity": "MEDIUM",
"confidentialityRequirement": "NOT_DEFINED",
"exploitMaturity": "UNREPORTED",
"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:A/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:U/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": "HIGH",
"vulnConfidentialityImpact": "HIGH",
"vulnIntegrityImpact": "HIGH",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "security-advisories@github.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2025-27142",
"options": [
{
"exploitation": "none"
},
{
"automatable": "yes"
},
{
"technicalImpact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-02-26T16:20:54.612459Z",
"version": "2.0.3"
}
}
]
},
"published": "2025-02-25T20:15:37.847",
"references": [
{
"source": "security-advisories@github.com",
"tags": [
"Patch"
],
"url": "https://github.com/localsend/localsend/commit/e8635204ec782ded45bc7d698deb60f3c4105687"
},
{
"source": "security-advisories@github.com",
"tags": [
"Vendor Advisory"
],
"url": "https://github.com/localsend/localsend/security/advisories/GHSA-f7jp-p6j4-3522"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Analyzed",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-22"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
}
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Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
How durations are calculated
Following the VTEM framework (Black Hat USA 2015), time to patch starts when the vendor or a coordinator was informed, total time to patch at discovery, and disclosure to patch at public disclosure; vendor response time runs from the report to its acknowledgement. Time to exploit and time unpatched start at the earliest discovery or report, falling back to public disclosure. Unpatched time ends at the first recorded patch, or the calculation time when no patch is recorded. Exploitation to patch shows the interval between those two events; a published proof of concept is a public exploit, not exploitation.
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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.