GSD-2017-17105
Vulnerability from gsd - Updated: 2023-12-13 01:21Details
Zivif PR115-204-P-RS V2.3.4.2103 and V4.7.4.2121 (and possibly in-between versions) web cameras are vulnerable to unauthenticated, blind remote command injection via CGI scripts used as part of the web interface, as demonstrated by a cgi-bin/iptest.cgi?cmd=iptest.cgi&-time="1504225666237"&-url=$(reboot) request.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2017-17105",
"description": "Zivif PR115-204-P-RS V2.3.4.2103 and V4.7.4.2121 (and possibly in-between versions) web cameras are vulnerable to unauthenticated, blind remote command injection via CGI scripts used as part of the web interface, as demonstrated by a cgi-bin/iptest.cgi?cmd=iptest.cgi\u0026-time=\"1504225666237\"\u0026-url=$(reboot) request.",
"id": "GSD-2017-17105",
"references": [
"https://packetstormsecurity.com/files/cve/CVE-2017-17105"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
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],
"details": "Zivif PR115-204-P-RS V2.3.4.2103 and V4.7.4.2121 (and possibly in-between versions) web cameras are vulnerable to unauthenticated, blind remote command injection via CGI scripts used as part of the web interface, as demonstrated by a cgi-bin/iptest.cgi?cmd=iptest.cgi\u0026-time=\"1504225666237\"\u0026-url=$(reboot) request.",
"id": "GSD-2017-17105",
"modified": "2023-12-13T01:21:04.600843Z",
"schema_version": "1.4.0"
}
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"affects": {
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{
"name": "20171212 Three exploits for Zivif Web Cameras (may impact others)",
"refsource": "FULLDISC",
"url": "http://seclists.org/fulldisclosure/2017/Dec/42"
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{
"name": "http://packetstormsecurity.com/files/158120/Zivif-Camera-2.3.4.2103-iptest.cgi-Blind-Remote-Command-Execution.html",
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"url": "http://packetstormsecurity.com/files/158120/Zivif-Camera-2.3.4.2103-iptest.cgi-Blind-Remote-Command-Execution.html"
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"url": "http://packetstormsecurity.com/files/158120/Zivif-Camera-2.3.4.2103-iptest.cgi-Blind-Remote-Command-Execution.html"
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},
"impact": {
"baseMetricV2": {
"acInsufInfo": false,
"cvssV2": {
"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": {
"cvssV3": {
"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"
},
"exploitabilityScore": 3.9,
"impactScore": 5.9
}
},
"lastModifiedDate": "2020-06-16T22:15Z",
"publishedDate": "2017-12-19T02:29Z"
}
}
}
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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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