FKIE_CVE-2018-16885
Vulnerability from fkie_nvd - Published: 2019-01-03 16:29 - Updated: 2026-06-17 01:44
Severity
4.7 (Medium) - CVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:H
5.5 (Medium) - CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
5.5 (Medium) - CVSS:3.0/
Summary
A flaw was found in the Linux kernel that allows the userspace to call memcpy_fromiovecend() and similar functions with a zero offset and buffer length which causes the read beyond the buffer boundaries, in certain cases causing a memory access fault and a system halt by accessing invalid memory address. This issue only affects kernel version 3.10.x as shipped with Red Hat Enterprise Linux 7.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| linux | linux_kernel | * | |
| redhat | enterprise_linux_server | 7.0 |
{
"affected": [
{
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"vendor": "The Linux Foundation",
"versions": [
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"status": "affected",
"version": "3.10.x as shipped with Red Hat Enterprise Linux 7"
}
]
}
],
"source": "secalert@redhat.com"
}
],
"configurations": [
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"value": "A flaw was found in the Linux kernel that allows the userspace to call memcpy_fromiovecend() and similar functions with a zero offset and buffer length which causes the read beyond the buffer boundaries, in certain cases causing a memory access fault and a system halt by accessing invalid memory address. This issue only affects kernel version 3.10.x as shipped with Red Hat Enterprise Linux 7."
},
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"lang": "es",
"value": "Se ha detectado un fallo en el kernel de Linux que permite al espacio de usuario llamar a memcpy_fromiovecend() y funciones similares con un offset de 0 y un tama\u00f1o de b\u00fafer que causa la lectura fuera de los l\u00edmites de dicho b\u00fafer. En algunos casos, esto provoca un fallo de acceso a la memoria y la detenci\u00f3n del sistema, accediendo a direcciones de memoria inv\u00e1lidas. Este problema solo afecta a las versiones 3.10.x del kernel, incluidas por defecto en Red Hat Enterprise Linux 7."
}
],
"id": "CVE-2018-16885",
"lastModified": "2026-06-17T01:44:59.667",
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"published": "2019-01-03T16:29:00.477",
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}
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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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