GSD-2023-34344
Vulnerability from gsd - Updated: 2023-12-13 01:20Details
AMI BMC contains a vulnerability in the IPMI
handler, where an unauthorized attacker can use certain oracles to guess a
valid username, which may lead to information disclosure.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2023-34344",
"id": "GSD-2023-34344"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2023-34344"
],
"details": "AMI BMC contains a vulnerability in the IPMI\nhandler, where an unauthorized attacker can use certain oracles to guess a\nvalid username, which may lead to information disclosure.\n\n\n\n\n\n",
"id": "GSD-2023-34344",
"modified": "2023-12-13T01:20:30.543977Z",
"schema_version": "1.4.0"
}
},
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"affects": {
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{
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"product_data": [
{
"product_name": "MegaRAC_SPx",
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{
"version_affected": "\u003c",
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},
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}
]
},
"generator": {
"engine": "Vulnogram 0.1.0-dev"
},
"impact": {
"cvss": [
{
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 5.3,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N",
"version": "3.1"
}
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"lang": "eng",
"value": "CWE-203 Observable Discrepancy"
}
]
},
{
"description": [
{
"lang": "eng",
"value": "CWe-208 Observable Timing Discrepancy"
}
]
}
]
},
"references": {
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"name": "https://9443417.fs1.hubspotusercontent-na1.net/hubfs/9443417/Security%20Advisories/AMI-SA-2023005.pdf",
"refsource": "MISC",
"url": "https://9443417.fs1.hubspotusercontent-na1.net/hubfs/9443417/Security%20Advisories/AMI-SA-2023005.pdf"
}
]
},
"source": {
"discovery": "UNKNOWN"
}
},
"nvd.nist.gov": {
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"nodes": [
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"cpe23Uri": "cpe:2.3:a:ami:megarac_sp-x:*:*:*:*:*:*:*:*",
"cpe_name": [],
"versionEndExcluding": "12.7",
"versionStartIncluding": "12.0",
"vulnerable": true
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{
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"versionEndExcluding": "13.5",
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"description": {
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"value": "AMI BMC contains a vulnerability in the IPMI\nhandler, where an unauthorized attacker can use certain oracles to guess a\nvalid username, which may lead to information disclosure.\n\n\n\n\n\n"
}
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},
"problemtype": {
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"references": {
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"name": "https://9443417.fs1.hubspotusercontent-na1.net/hubfs/9443417/Security%20Advisories/AMI-SA-2023005.pdf",
"refsource": "MISC",
"tags": [
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"url": "https://9443417.fs1.hubspotusercontent-na1.net/hubfs/9443417/Security%20Advisories/AMI-SA-2023005.pdf"
}
]
}
},
"impact": {
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 5.3,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 1.4
}
},
"lastModifiedDate": "2023-06-20T14:07Z",
"publishedDate": "2023-06-12T17:15Z"
}
}
}
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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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