FKIE_CVE-2015-7222
Vulnerability from fkie_nvd - Published: 2015-12-16 11:59 - Updated: 2026-06-17 00:32
Severity
Summary
Integer underflow in the Metadata::setData function in MetaData.cpp in libstagefright in Mozilla Firefox before 43.0 and Firefox ESR 38.x before 38.5 allows remote attackers to execute arbitrary code or cause a denial of service (incorrect memory allocation and application crash) via an MP4 video file with crafted covr metadata that triggers a buffer overflow.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| mozilla | firefox | 38.0 | |
| mozilla | firefox | 38.0.1 | |
| mozilla | firefox | 38.0.5 | |
| mozilla | firefox | 38.1.0 | |
| mozilla | firefox | 38.1.1 | |
| mozilla | firefox | 38.2.0 | |
| mozilla | firefox | 38.2.1 | |
| mozilla | firefox | 38.3.0 | |
| mozilla | firefox | 38.4.0 | |
| opensuse | leap | 42.1 | |
| opensuse | opensuse | 13.1 | |
| opensuse | opensuse | 13.2 | |
| fedoraproject | fedora | 22 | |
| fedoraproject | fedora | 23 | |
| mozilla | firefox | * |
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"value": "Integer underflow in the Metadata::setData function in MetaData.cpp in libstagefright in Mozilla Firefox before 43.0 and Firefox ESR 38.x before 38.5 allows remote attackers to execute arbitrary code or cause a denial of service (incorrect memory allocation and application crash) via an MP4 video file with crafted covr metadata that triggers a buffer overflow."
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"value": "Desbordamiento inferior de entero en la funci\u00f3n Metadata::setData en MetaData.cpp en libstagefright en Mozilla Firefox en versiones anteriores a 43.0 y Firefox ESR 38.x en versiones anteriores a 38.5 permite a atacantes remotos ejecutar c\u00f3digo arbitrario o causar una denegaci\u00f3n de servicio (asignaci\u00f3n de memoria incorrecta y ca\u00edda de aplicaci\u00f3n) a trav\u00e9s de un archivo de v\u00eddeo MP4 con metadatos covr manipulados que desencadena un desbordamiento de buffer."
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"id": "CVE-2015-7222",
"lastModified": "2026-06-17T00:32:04.627",
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"source": "nvd@nist.gov",
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"published": "2015-12-16T11:59:20.370",
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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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