VAR-201604-0443
Vulnerability from variot - Updated: 2025-04-12 23:32Integer overflow in Huawei P7 phones with software before P7-L07 V100R001C01B606 allows remote attackers to gain privileges via a crafted application with the system or camera permission. HuaweiSmartPhones7 is a smart phone from China Huawei. HuaweiSmartPhones7 has a local privilege escalation vulnerability. A local attacker can exploit this vulnerability to gain root privileges. The Huawei P7 is a smartphone from the Chinese company Huawei. An integer overflow vulnerability exists in the Huawei P7 that uses software versions earlier than P7-L07 V100R001C01B606
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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.
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- Patched: The vulnerability was 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
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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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