GSD-2023-28506
Vulnerability from gsd - Updated: 2023-12-13 01:20Details
Rocket Software UniData versions prior to 8.2.4 build 3003 and UniVerse versions prior to 11.3.5 build 1001 or 12.2.1 build 2002 suffer from a stack-based buffer overflow, where a string is copied into a buffer using a memcpy-like function and a user-provided length. This requires a valid login to exploit.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2023-28506",
"id": "GSD-2023-28506"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
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],
"details": "Rocket Software UniData versions prior to 8.2.4 build 3003 and UniVerse versions prior to 11.3.5 build 1001 or 12.2.1 build 2002 suffer from a stack-based buffer overflow, where a string is copied into a buffer using a memcpy-like function and a user-provided length. This requires a valid login to exploit.",
"id": "GSD-2023-28506",
"modified": "2023-12-13T01:20:47.428857Z",
"schema_version": "1.4.0"
}
},
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},
"affects": {
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{
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{
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"version": {
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{
"version_affected": "\u003c",
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}
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},
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"credits": [
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"value": "Ron Bowes"
}
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}
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},
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"problemtype": {
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{
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"lang": "eng",
"value": "CWE-120 Buffer Copy without Checking Size of Input (\u0027Classic Buffer Overflow\u0027)"
}
]
}
]
},
"references": {
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{
"name": "https://www.rapid7.com/blog/post/2023/03/29/multiple-vulnerabilities-in-rocket-software-unirpc-server-fixed/",
"refsource": "MISC",
"url": "https://www.rapid7.com/blog/post/2023/03/29/multiple-vulnerabilities-in-rocket-software-unirpc-server-fixed/"
}
]
},
"source": {
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}
},
"nvd.nist.gov": {
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},
"impact": {
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 5.9
}
},
"lastModifiedDate": "2023-04-06T16:51Z",
"publishedDate": "2023-03-29T21:15Z"
}
}
}
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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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