FKIE_CVE-2021-25337
Vulnerability from fkie_nvd - Published: 2021-03-04 21:15 - Updated: 2026-06-17 03:41
Severity
4.4 (Medium) - CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:L/I:L/A:N
7.1 (High) - CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:N
7.1 (High) - CVSS:3.1/
Summary
Improper access control in clipboard service in Samsung mobile devices prior to SMR Mar-2021 Release 1 allows untrusted applications to read or write certain local files.
References
Impacted products
{
"affected": [
{
"affectedData": [
{
"product": "Samsung Mobile Devices",
"vendor": "Samsung Mobile",
"versions": [
{
"lessThan": "SMR Mar-2021 Release 1",
"status": "affected",
"version": "Selected P(9.0), Q(10.0), R(11.0)",
"versionType": "custom"
}
]
}
],
"source": "mobile.security@samsung.com"
}
],
"cisaActionDue": "2022-11-29",
"cisaExploitAdd": "2022-11-08",
"cisaRequiredAction": "Apply updates per vendor instructions.",
"cisaVulnerabilityName": "Samsung Mobile Devices Improper Access Control Vulnerability",
"configurations": [
{
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"negate": false,
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}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Improper access control in clipboard service in Samsung mobile devices prior to SMR Mar-2021 Release 1 allows untrusted applications to read or write certain local files."
},
{
"lang": "es",
"value": "Un control de acceso inapropiado en el servicio clipboard en los dispositivos m\u00f3viles Samsung anteriores a SMR Mar-2021 Release 1, permite que las aplicaciones no confiables lean o escriban ciertos archivos locales"
}
],
"id": "CVE-2021-25337",
"lastModified": "2026-06-17T03:41:53.733",
"metrics": {
"cvssMetricV2": [
{
"acInsufInfo": false,
"baseSeverity": "MEDIUM",
"cvssData": {
"accessComplexity": "MEDIUM",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "NONE",
"baseScore": 5.8,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:M/Au:N/C:P/I:P/A:N",
"version": "2.0"
},
"exploitabilityScore": 8.6,
"impactScore": 4.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"source": "nvd@nist.gov",
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}
],
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"attackVector": "LOCAL",
"availabilityImpact": "NONE",
"baseScore": 4.4,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:L/I:L/A:N",
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},
{
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"baseScore": 7.1,
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},
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"ssvcV203": [
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"ssvcData": {
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"options": [
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{
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{
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],
"role": "CISA Coordinator",
"timestamp": "2025-02-04T21:26:40.665748Z",
"version": "2.0.3"
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}
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},
"published": "2021-03-04T21:15:13.667",
"references": [
{
"source": "mobile.security@samsung.com",
"tags": [
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"url": "https://security.samsungmobile.com"
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{
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"vulnStatus": "Analyzed",
"weaknesses": [
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{
"lang": "en",
"value": "CWE-269"
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"source": "nvd@nist.gov",
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]
}
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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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