CVE-2021-0675 (GCVE-0-2021-0675)
Vulnerability from cvelistv5 – Published: 2021-12-15 18:05 – Updated: 2024-08-03 15:47
VLAI
EPSS
VEX
Summary
In alac decoder, there is a possible out of bounds write due to an incorrect bounds check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS06064258; Issue ID: ALPS06064258.
Severity
7.8 (High)
CWE
- Elevation of Privilege
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://corp.mediatek.com/product-security-bullet… | x_refsource_MISC |
Impacted products
1 product
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"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "In alac decoder, there is a possible out of bounds write due to an incorrect bounds check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS06064258; Issue ID: ALPS06064258."
},
{
"lang": "es",
"value": "En el decodificador alac, existe una posible escritura fuera de l\u00edmites debido a una comprobaci\u00f3n de l\u00edmites incorrecta. Esto podr\u00eda llevar a una escalada local de privilegios sin necesidad de privilegios de ejecuci\u00f3n adicionales. La interacci\u00f3n del usuario no es necesaria para la explotaci\u00f3n. ID del parche: ALPS06064258; ID del problema: ALPS06064258"
}
],
"id": "CVE-2021-0675",
"lastModified": "2024-11-21T05:43:07.663",
"metrics": {
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{
"acInsufInfo": false,
"baseSeverity": "HIGH",
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"accessVector": "LOCAL",
"authentication": "NONE",
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"vectorString": "AV:L/AC:L/Au:N/C:C/I:C/A:C",
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},
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"source": "nvd@nist.gov",
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"source": "security@android.com",
"tags": [
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"description": [
{
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"value": "CWE-787"
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"current_release_date": "2026-03-27T15:12:12+00:00",
"cve": "CVE-2021-0675",
"id": "CVE-2021-0675",
"initial_release_date": "2021-01-01T00:00:00+00:00",
"product_status:known_not_affected": "1",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "CVE-2021-0675",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2021/cve-2021-0675.json",
"version": "3"
}
}
}
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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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