GSD-2014-7857
Vulnerability from gsd - Updated: 2023-12-13 01:22Details
D-Link DNS-320L firmware before 1.04b12, DNS-327L before 1.03b04 Build0119, DNR-326 1.40b03, DNS-320B 1.02b01, DNS-345 1.03b06, DNS-325 1.05b03, and DNS-322L 2.00b07 allow remote attackers to bypass authentication and log in with administrator permissions by passing the cgi_set_wto command in the cmd parameter, and setting the spawned session's cookie to username=admin.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2014-7857",
"description": "D-Link DNS-320L firmware before 1.04b12, DNS-327L before 1.03b04 Build0119, DNR-326 1.40b03, DNS-320B 1.02b01, DNS-345 1.03b06, DNS-325 1.05b03, and DNS-322L 2.00b07 allow remote attackers to bypass authentication and log in with administrator permissions by passing the cgi_set_wto command in the cmd parameter, and setting the spawned session\u0027s cookie to username=admin.",
"id": "GSD-2014-7857"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
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],
"details": "D-Link DNS-320L firmware before 1.04b12, DNS-327L before 1.03b04 Build0119, DNR-326 1.40b03, DNS-320B 1.02b01, DNS-345 1.03b06, DNS-325 1.05b03, and DNS-322L 2.00b07 allow remote attackers to bypass authentication and log in with administrator permissions by passing the cgi_set_wto command in the cmd parameter, and setting the spawned session\u0027s cookie to username=admin.",
"id": "GSD-2014-7857",
"modified": "2023-12-13T01:22:47.831240Z",
"schema_version": "1.4.0"
}
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"impact": {
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"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "COMPLETE",
"baseScore": 10.0,
"confidentialityImpact": "COMPLETE",
"integrityImpact": "COMPLETE",
"vectorString": "AV:N/AC:L/Au:N/C:C/I:C/A:C",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 10.0,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "HIGH",
"userInteractionRequired": false
},
"baseMetricV3": {
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"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.0"
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"exploitabilityScore": 3.9,
"impactScore": 5.9
}
},
"lastModifiedDate": "2023-04-26T18:55Z",
"publishedDate": "2017-08-25T18:29Z"
}
}
}
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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 |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
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- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
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- 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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