GSD-2022-2471
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
Stack-based Buffer Overflow vulnerability in the EZVIZ Motion Detection component as used in camera models CS-CV248, CS-C6N-A0-1C2WFR, CS-DB1C-A0-1E2W2FR, CS-C6N-B0-1G2WF, CS-C3W-A0-3H4WFRL allows a remote attacker to execute remote code on the device. This issue affects: EZVIZ CS-CV248 versions prior to 5.2.3 build 220725. EZVIZ CS-C6N-A0-1C2WFR versions prior to 5.3.0 build 220428. EZVIZ CS-DB1C-A0-1E2W2FR versions prior to 5.3.0 build 220802. EZVIZ CS-C6N-B0-1G2WF versions prior to 5.3.0 build 220712. EZVIZ CS-C3W-A0-3H4WFRL versions prior to 5.3.5 build 220723.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2022-2471",
"description": "Stack-based Buffer Overflow vulnerability in the EZVIZ Motion Detection component as used in camera models CS-CV248, CS-C6N-A0-1C2WFR, CS-DB1C-A0-1E2W2FR, CS-C6N-B0-1G2WF, CS-C3W-A0-3H4WFRL allows a remote attacker to execute remote code on the device. This issue affects: EZVIZ CS-CV248 versions prior to 5.2.3 build 220725. EZVIZ CS-C6N-A0-1C2WFR versions prior to 5.3.0 build 220428. EZVIZ CS-DB1C-A0-1E2W2FR versions prior to 5.3.0 build 220802. EZVIZ CS-C6N-B0-1G2WF versions prior to 5.3.0 build 220712. EZVIZ CS-C3W-A0-3H4WFRL versions prior to 5.3.5 build 220723.",
"id": "GSD-2022-2471"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2022-2471"
],
"details": "Stack-based Buffer Overflow vulnerability in the EZVIZ Motion Detection component as used in camera models CS-CV248, CS-C6N-A0-1C2WFR, CS-DB1C-A0-1E2W2FR, CS-C6N-B0-1G2WF, CS-C3W-A0-3H4WFRL allows a remote attacker to execute remote code on the device. This issue affects: EZVIZ CS-CV248 versions prior to 5.2.3 build 220725. EZVIZ CS-C6N-A0-1C2WFR versions prior to 5.3.0 build 220428. EZVIZ CS-DB1C-A0-1E2W2FR versions prior to 5.3.0 build 220802. EZVIZ CS-C6N-B0-1G2WF versions prior to 5.3.0 build 220712. EZVIZ CS-C3W-A0-3H4WFRL versions prior to 5.3.5 build 220723.",
"id": "GSD-2022-2471",
"modified": "2023-12-13T01:19:19.563420Z",
"schema_version": "1.4.0"
}
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"TITLE": "Stack-Based Buffer Overflow Vulnerability in the EZVIZ Motion Detection component"
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"baseScore": 9.9,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "CHANGED",
"userInteraction": "NONE",
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"url": "https://www.bitdefender.com/blog/labs/vulnerabilities-identified-in-ezviz-smart-cams"
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"solution": [
{
"lang": "eng",
"value": "Firmware versions for each product model that fixes the vulnerability are available below:\n\nEZVIZ CS-CV248 version 5.2.3 build 220725 and newer.\nEZVIZ CS-C6N-A0-1C2WFR version 5.3.0 build 220428 and newer.\nEZVIZ CS-DB1C-A0-1E2W2FR version 5.3.0 build 220802 and newer.\nEZVIZ CS-C6N-B0-1G2WF version 5.3.0 build 220712 and newer.\nEZVIZ CS-C3W-A0-3H4WFRL version 5.3.5 build 220723 and newer."
}
],
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"lastModifiedDate": "2022-09-20T18:48Z",
"publishedDate": "2022-09-15T14:15Z"
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}
}
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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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