CVE-2021-32941 (GCVE-0-2021-32941)
Vulnerability from cvelistv5 – Published: 2022-05-23 18:51 – Updated: 2025-04-16 16:19
VLAI
EPSS
VEX
Title
Annke Network Video Recorder - Stack-based Buffer Overflow
Summary
Annke N48PBB (Network Video Recorder) products of version 3.4.106 build 200422 and prior are vulnerable to a stack-based buffer overflow, which allows an unauthorized remote attacker to execute arbitrary code with the same privileges as the server user (root).
Severity
9.4 (Critical)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-04-16 15:55 UTC
CWE
- CWE-121 - Stack-based Buffer Overflow
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://www.cisa.gov/uscert/ics/advisories/icsa-2… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Annke | N48PBB (NVR) |
Affected:
All , ≤ V3.4.106 build 200422
(custom)
|
guessed |
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},
"generator": {
"engine": "Vulnogram 0.0.9"
},
"impact": {
"cvss": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.4,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "LOW",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:H/A:H",
"version": "3.1"
}
},
"problemtype": {
"problemtype_data": [
{
"description": [
{
"lang": "eng",
"value": "CWE-121 Stack-based Buffer Overflow"
}
]
}
]
},
"references": {
"reference_data": [
{
"name": "https://www.cisa.gov/uscert/ics/advisories/icsa-21-238-02",
"refsource": "MISC",
"url": "https://www.cisa.gov/uscert/ics/advisories/icsa-21-238-02"
}
]
},
"source": {
"advisory": "ICSA-21-238-02",
"discovery": "UNKNOWN"
}
}
}
},
"cveMetadata": {
"assignerOrgId": "7d14cffa-0d7d-4270-9dc0-52cabd5a23a6",
"assignerShortName": "icscert",
"cveId": "CVE-2021-32941",
"datePublished": "2022-05-23T18:51:57.000Z",
"dateReserved": "2021-05-13T00:00:00.000Z",
"dateUpdated": "2025-04-16T16:19:18.611Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
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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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