FKIE_CVE-2015-5936
Vulnerability from fkie_nvd - Published: 2015-10-23 21:59 - Updated: 2026-06-17 00:30
Severity
Summary
ImageIO in Apple iOS before 9.1, OS X before 10.11.1, and watchOS before 2.0.1 allows remote attackers to execute arbitrary code or cause a denial of service (memory corruption) via crafted metadata in an image, a different vulnerability than CVE-2015-5935, CVE-2015-5937, and CVE-2015-5939.
References
{
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"cveTags": [],
"descriptions": [
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"value": "ImageIO in Apple iOS before 9.1, OS X before 10.11.1, and watchOS before 2.0.1 allows remote attackers to execute arbitrary code or cause a denial of service (memory corruption) via crafted metadata in an image, a different vulnerability than CVE-2015-5935, CVE-2015-5937, and CVE-2015-5939."
},
{
"lang": "es",
"value": "ImageIO en Apple iOS en versiones anteriores a 9.1, OS X en versiones anteriores a 10.11.1 y watchOS en versiones anteriores a 2.0.1 permite a atacantes remotos ejecutar c\u00f3digo arbitrario o provocar una denegaci\u00f3n de servicio (corrupci\u00f3n de memoria) a trav\u00e9s de metadatos manipulados en una imagen, una vulnerabilidad diferente a CVE-2015-5935, CVE-2015-5937 y CVE-2015-5939."
}
],
"id": "CVE-2015-5936",
"lastModified": "2026-06-17T00:30:08.560",
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"source": "nvd@nist.gov",
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"published": "2015-10-23T21:59:13.130",
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"vulnStatus": "Modified",
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]
}
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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.
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- 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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