GSD-2017-14011
Vulnerability from gsd - Updated: 2023-12-13 01:21Details
A Cross-Site Request Forgery issue was discovered in ProMinent MultiFLEX M10a Controller web interface. The application does not sufficiently verify requests, making it susceptible to cross-site request forgery. This may allow an attacker to execute unauthorized code, resulting in changes to the configuration of the device.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2017-14011",
"description": "A Cross-Site Request Forgery issue was discovered in ProMinent MultiFLEX M10a Controller web interface. The application does not sufficiently verify requests, making it susceptible to cross-site request forgery. This may allow an attacker to execute unauthorized code, resulting in changes to the configuration of the device.",
"id": "GSD-2017-14011"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2017-14011"
],
"details": "A Cross-Site Request Forgery issue was discovered in ProMinent MultiFLEX M10a Controller web interface. The application does not sufficiently verify requests, making it susceptible to cross-site request forgery. This may allow an attacker to execute unauthorized code, resulting in changes to the configuration of the device.",
"id": "GSD-2017-14011",
"modified": "2023-12-13T01:21:13.007395Z",
"schema_version": "1.4.0"
}
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}
]
},
"problemtype": {
"problemtype_data": [
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"description": [
{
"lang": "eng",
"value": "CWE-352"
}
]
}
]
},
"references": {
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"name": "101259",
"refsource": "BID",
"url": "http://www.securityfocus.com/bid/101259"
},
{
"name": "https://ics-cert.us-cert.gov/advisories/ICSA-17-285-01",
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"impact": {
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"obtainOtherPrivilege": false,
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"userInteractionRequired": true
},
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"attackVector": "NETWORK",
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"baseScore": 8.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
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},
"lastModifiedDate": "2019-10-09T23:23Z",
"publishedDate": "2017-10-17T22:29Z"
}
}
}
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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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