FKIE_CVE-2017-1000407
Vulnerability from fkie_nvd - Published: 2017-12-11 21:29 - Updated: 2026-06-17 00:59
Severity
Summary
The Linux Kernel 2.6.32 and later are affected by a denial of service, by flooding the diagnostic port 0x80 an exception can be triggered leading to a kernel panic.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| redhat | virtualization_host | 4.0 | |
| redhat | enterprise_linux_desktop | 7.0 | |
| redhat | enterprise_linux_server | 7.0 | |
| redhat | enterprise_linux_server_aus | 7.6 | |
| redhat | enterprise_linux_server_eus | 7.6 | |
| redhat | enterprise_linux_server_tus | 7.6 | |
| redhat | enterprise_linux_workstation | 7.0 | |
| linux | linux_kernel | * | |
| linux | linux_kernel | 4.15 | |
| linux | linux_kernel | 4.15 | |
| debian | debian_linux | 7.0 | |
| debian | debian_linux | 8.0 | |
| debian | debian_linux | 9.0 | |
| canonical | ubuntu_linux | 12.04 | |
| canonical | ubuntu_linux | 14.04 | |
| canonical | ubuntu_linux | 16.04 | |
| canonical | ubuntu_linux | 17.10 |
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"cveTags": [],
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"lang": "en",
"value": "The Linux Kernel 2.6.32 and later are affected by a denial of service, by flooding the diagnostic port 0x80 an exception can be triggered leading to a kernel panic."
},
{
"lang": "es",
"value": "El kernel de Linux en versiones 2.6.32 y posteriores se ha visto afectado por una denegaci\u00f3n de servicio (DoS): al inundar el puerto de diagn\u00f3stico 0x80 puede ocurrir una excepci\u00f3n que conduce a una situaci\u00f3n de p\u00e1nico del kernel."
}
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"id": "CVE-2017-1000407",
"lastModified": "2026-06-17T00:59:07.070",
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"accessVector": "ADJACENT_NETWORK",
"authentication": "NONE",
"availabilityImpact": "COMPLETE",
"baseScore": 6.1,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:A/AC:L/Au:N/C:N/I:N/A:C",
"version": "2.0"
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"exploitabilityScore": 6.5,
"impactScore": 6.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
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"scope": "CHANGED",
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"published": "2017-12-11T21:29:00.297",
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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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