VAR-201601-0395
Vulnerability from variot - Updated: 2025-04-13 23:37Heap-based buffer overflow in the HIFI driver in Huawei Mate 7 phones with software MT7-UL00 before MT7-UL00C17B354, MT7-TL10 before MT7-TL10C00B354, MT7-TL00 before MT7-TL00C01B354, and MT7-CL00 before MT7-CL00C92B354 and P8 phones with software GRA-TL00 before GRA-TL00C01B220SP01, GRA-CL00 before GRA-CL00C92B220, GRA-CL10 before GRA-CL10C92B220, GRA-UL00 before GRA-UL00C00B220, and GRA-UL10 before GRA-UL10C00B220 allows attackers to cause a denial of service (reboot) or execute arbitrary code via a crafted application. Huawei Mate7 is a smartphone product from China's Huawei company. There is a memory heap overflow vulnerability in Huawei Mate7's HIFI driver. An attacker can use this vulnerability to entice a user to install a malicious application to read and modify memory data, causing the system to reboot or gain root access to the phone. Huawei Smart Phones are prone to a local heap-based buffer-overflow vulnerability because it fails to perform adequate boundary checks on user-supplied data. Local attackers can exploit this issue to execute arbitrary code in the context of the affected application. Failed exploit attempts will result in denial-of-service conditions. The Huawei Mate 7 and P8 are smartphones from the Chinese company Huawei. HIFI driver is one of the HIFI (High Fidelity) audio drivers. The following products and versions are affected: Huawei Mate 7 using software versions earlier than MT7-UL00C17B354, MT7-TL10C00B354, MT7-TL00C01B354, and MT7-CL00C92B354, using versions earlier than GRA-TL00C01B220SP01, versions earlier than GRA-CL00C92B220, Versions earlier than GRA-CL10C92B220, versions earlier than GRA-UL00C00B220, and P8 of software versions earlier than GRA-UL10C00B220
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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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