VAR-202108-0279
Vulnerability from variot - Updated: 2024-08-14 12:07Some Huawei Smartphones has an insufficient input validation vulnerability due to the lack of parameter validation. An attacker may trick a user into installing a malicious APP. The app can modify specific parameters, causing the system to crash. Affected product include:OxfordS-AN00A 10.0.1.10(C00E10R1P1),10.0.1.105(C00E103R3P3),10.0.1.115(C00E110R3P3),10.0.1.123(C00E121R3P3),10.0.1.135(C00E130R3P3),10.0.1.135(C00E130R4P1),10.0.1.152(C00E140R4P1),10.0.1.160(C00E160R4P1),10.0.1.167(C00E166R4P1),10.0.1.173(C00E172R5P1),10.0.1.178(C00E175R5P1) and 10.1.0.202(C00E79R5P1). Huawei smartphone OxfordS-AN00A Is vulnerable to input validation.Denial of service (DoS) It may be put into a state. Huawei OxfordS-AN00A is a smart phone of China's Huawei (Huawei) company. Pillow is a Python-based image processing library. There is currently no information about this vulnerability, please feel free to follow CNNVD or manufacturer announcements
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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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