GSD-2018-9145
Vulnerability from gsd - Updated: 2023-12-13 01:22Details
In the DataBuf class in include/exiv2/types.hpp in Exiv2 0.26, an issue exists in the constructor with an initial buffer size. A large size value may lead to a SIGABRT during an attempt at memory allocation. NOTE: some third parties have been unable to reproduce the SIGABRT when using the 4-DataBuf-abort-1 PoC file.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2018-9145",
"description": "In the DataBuf class in include/exiv2/types.hpp in Exiv2 0.26, an issue exists in the constructor with an initial buffer size. A large size value may lead to a SIGABRT during an attempt at memory allocation. NOTE: some third parties have been unable to reproduce the SIGABRT when using the 4-DataBuf-abort-1 PoC file.",
"id": "GSD-2018-9145",
"references": [
"https://www.suse.com/security/cve/CVE-2018-9145.html"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
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],
"details": "In the DataBuf class in include/exiv2/types.hpp in Exiv2 0.26, an issue exists in the constructor with an initial buffer size. A large size value may lead to a SIGABRT during an attempt at memory allocation. NOTE: some third parties have been unable to reproduce the SIGABRT when using the 4-DataBuf-abort-1 PoC file.",
"id": "GSD-2018-9145",
"modified": "2023-12-13T01:22:33.815955Z",
"schema_version": "1.4.0"
}
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"url": "https://bugzilla.novell.com/show_bug.cgi?id=1087879"
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{
"name": "https://github.com/xiaoqx/pocs/tree/master/exiv2",
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"url": "https://github.com/xiaoqx/pocs/tree/master/exiv2"
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{
"name": "GLSA-201811-14",
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"impact": {
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"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 4.3,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:M/Au:N/C:N/I:N/A:P",
"version": "2.0"
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"exploitabilityScore": 8.6,
"impactScore": 2.9,
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"severity": "MEDIUM",
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"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
"version": "3.0"
},
"exploitabilityScore": 2.8,
"impactScore": 3.6
}
},
"lastModifiedDate": "2019-03-27T19:23Z",
"publishedDate": "2018-03-30T08:29Z"
}
}
}
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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
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Nomenclature
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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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