GSD-2013-5550
Vulnerability from gsd - Updated: 2023-12-13 01:22Details
The fabric-interconnect component in Cisco Unified Computing System (UCS) allows local users to cause a denial of service via crafted command parameters that trigger hardware-component write operations, aka Bug ID CSCtq86549.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2013-5550",
"description": "The fabric-interconnect component in Cisco Unified Computing System (UCS) allows local users to cause a denial of service via crafted command parameters that trigger hardware-component write operations, aka Bug ID CSCtq86549.",
"id": "GSD-2013-5550"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
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],
"details": "The fabric-interconnect component in Cisco Unified Computing System (UCS) allows local users to cause a denial of service via crafted command parameters that trigger hardware-component write operations, aka Bug ID CSCtq86549.",
"id": "GSD-2013-5550",
"modified": "2023-12-13T01:22:21.517469Z",
"schema_version": "1.4.0"
}
},
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},
"affects": {
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{
"product": {
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"version": {
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"references": {
"reference_data": [
{
"name": "20131021 Cisco Unified Computing System Fabric Interconnect Denial of Service Vulnerability",
"refsource": "CISCO",
"url": "http://tools.cisco.com/security/center/content/CiscoSecurityNotice/CVE-2013-5550"
}
]
}
},
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"nodes": [
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"cpe_match": [
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"cve": {
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},
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"description": {
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"references": {
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{
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"tags": [
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],
"url": "http://tools.cisco.com/security/center/content/CiscoSecurityNotice/CVE-2013-5550"
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}
},
"impact": {
"baseMetricV2": {
"cvssV2": {
"accessComplexity": "LOW",
"accessVector": "LOCAL",
"authentication": "SINGLE",
"availabilityImpact": "COMPLETE",
"baseScore": 4.6,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:L/AC:L/Au:S/C:N/I:N/A:C",
"version": "2.0"
},
"exploitabilityScore": 3.1,
"impactScore": 6.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": false
}
},
"lastModifiedDate": "2013-10-22T18:07Z",
"publishedDate": "2013-10-22T11:17Z"
}
}
}
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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.
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- 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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