GSD-2019-3937
Vulnerability from gsd - Updated: 2023-12-13 01:24Details
Crestron AM-100 with firmware 1.6.0.2 and AM-101 with firmware 2.7.0.2 stores usernames, passwords, slideshow passcode, and other configuration options in cleartext in the file /tmp/scfgdndf. A local attacker can use this vulnerability to recover sensitive data.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2019-3937",
"description": "Crestron AM-100 with firmware 1.6.0.2 and AM-101 with firmware 2.7.0.2 stores usernames, passwords, slideshow passcode, and other configuration options in cleartext in the file /tmp/scfgdndf. A local attacker can use this vulnerability to recover sensitive data.",
"id": "GSD-2019-3937"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2019-3937"
],
"details": "Crestron AM-100 with firmware 1.6.0.2 and AM-101 with firmware 2.7.0.2 stores usernames, passwords, slideshow passcode, and other configuration options in cleartext in the file /tmp/scfgdndf. A local attacker can use this vulnerability to recover sensitive data.",
"id": "GSD-2019-3937",
"modified": "2023-12-13T01:24:04.531076Z",
"schema_version": "1.4.0"
}
},
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}
]
},
"problemtype": {
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"value": "CWE-312: Cleartext Storage"
}
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"refsource": "MISC",
"url": "https://www.tenable.com/security/research/tra-2019-20"
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"impact": {
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"authentication": "NONE",
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"baseScore": 2.1,
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"integrityImpact": "NONE",
"vectorString": "AV:L/AC:L/Au:N/C:P/I:N/A:N",
"version": "2.0"
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"exploitabilityScore": 3.9,
"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "LOW",
"userInteractionRequired": false
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"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
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},
"lastModifiedDate": "2020-10-16T16:03Z",
"publishedDate": "2019-04-30T21:29Z"
}
}
}
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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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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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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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