VAR-201702-1057
Vulnerability from variot - Updated: 2023-12-18 12:20The web interface on Dahua DHI-HCVR7216A-S3 devices with NVR Firmware 3.210.0001.10 2016-06-06, Camera Firmware 2.400.0000.28.R 2016-03-29, and SmartPSS Software 1.16.1 2017-01-19 allows remote attackers to obtain login access by leveraging knowledge of the MD5 Admin Hash without knowledge of the corresponding password, a different vulnerability than CVE-2013-6117. Dahua DHI-HCVR7216A-S3 is a network hard disk recorder product of Dahua Company of China. There is a security hole in the web interface of Dahua DHI-HCVR7216A-S3 device. A remote attacker can exploit a vulnerability to submit a special request that does not authorize access to the device. Dahua Security DVR Appliances are prone to an authentication-bypass vulnerability. An attacker can exploit this issue to bypass the authentication mechanism and perform unauthorized actions. This may aid in further attacks
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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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