GSD-2015-3836
Vulnerability from gsd - Updated: 2023-12-13 01:20Details
The Parse_wave function in arm-wt-22k/lib_src/eas_mdls.c in the Sonivox DLS-to-EAS converter in Android before 5.1.1 LMY48I does not reject a negative value for a certain size field, which allows remote attackers to execute arbitrary code or cause a denial of service (buffer overflow) via crafted XMF data, aka internal bug 21132860.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2015-3836",
"description": "The Parse_wave function in arm-wt-22k/lib_src/eas_mdls.c in the Sonivox DLS-to-EAS converter in Android before 5.1.1 LMY48I does not reject a negative value for a certain size field, which allows remote attackers to execute arbitrary code or cause a denial of service (buffer overflow) via crafted XMF data, aka internal bug 21132860.",
"id": "GSD-2015-3836"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
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],
"details": "The Parse_wave function in arm-wt-22k/lib_src/eas_mdls.c in the Sonivox DLS-to-EAS converter in Android before 5.1.1 LMY48I does not reject a negative value for a certain size field, which allows remote attackers to execute arbitrary code or cause a denial of service (buffer overflow) via crafted XMF data, aka internal bug 21132860.",
"id": "GSD-2015-3836",
"modified": "2023-12-13T01:20:07.975719Z",
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}
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"name": "[android-security-updates] 20150812 Nexus Security Bulletin (August 2015)",
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"impact": {
"baseMetricV2": {
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"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "COMPLETE",
"baseScore": 10.0,
"confidentialityImpact": "COMPLETE",
"integrityImpact": "COMPLETE",
"vectorString": "AV:N/AC:L/Au:N/C:C/I:C/A:C",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 10.0,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "HIGH",
"userInteractionRequired": false
}
},
"lastModifiedDate": "2015-10-01T16:46Z",
"publishedDate": "2015-10-01T00:59Z"
}
}
}
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Sightings
| Author | Source | Type | Date | Other |
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Nomenclature
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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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