GSD-2020-3940
Vulnerability from gsd - Updated: 2023-12-13 01:22Details
VMware Workspace ONE SDK and dependent mobile application updates address sensitive information disclosure vulnerability.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2020-3940",
"description": "VMware Workspace ONE SDK and dependent mobile application updates address sensitive information disclosure vulnerability.",
"id": "GSD-2020-3940"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
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"CVE-2020-3940"
],
"details": "VMware Workspace ONE SDK and dependent mobile application updates address sensitive information disclosure vulnerability.",
"id": "GSD-2020-3940",
"modified": "2023-12-13T01:22:10.154490Z",
"schema_version": "1.4.0"
}
},
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"affects": {
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{
"product": {
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{
"product_name": "Workspace ONE SDK",
"version": {
"version_data": [
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"version_value": "Workspace ONE SDK for Android prior to 19.11.1 and Workspace ONE SDK for iOS (Objective-C) prior to 5.9.9.8"
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}
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},
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"refsource": "CONFIRM",
"url": "https://www.vmware.com/security/advisories/VMSA-2020-0001.html"
}
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}
},
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"description": {
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"tags": [
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"url": "https://www.vmware.com/security/advisories/VMSA-2020-0001.html"
}
]
}
},
"impact": {
"baseMetricV2": {
"acInsufInfo": false,
"cvssV2": {
"accessComplexity": "MEDIUM",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "NONE",
"baseScore": 4.3,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:M/Au:N/C:P/I:N/A:N",
"version": "2.0"
},
"exploitabilityScore": 8.6,
"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": false
},
"baseMetricV3": {
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"attackComplexity": "HIGH",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 5.9,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/A:N",
"version": "3.1"
},
"exploitabilityScore": 2.2,
"impactScore": 3.6
}
},
"lastModifiedDate": "2020-01-27T16:32Z",
"publishedDate": "2020-01-17T18:15Z"
}
}
}
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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 |
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Nomenclature
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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
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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.
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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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