GSD-2015-6525
Vulnerability from gsd - Updated: 2023-12-13 01:20Details
Multiple integer overflows in the evbuffer API in Libevent 2.0.x before 2.0.22 and 2.1.x before 2.1.5-beta allow context-dependent attackers to cause a denial of service or possibly have other unspecified impact via "insanely large inputs" to the (1) evbuffer_add, (2) evbuffer_prepend, (3) evbuffer_expand, (4) exbuffer_reserve_space, or (5) evbuffer_read function, which triggers a heap-based buffer overflow or an infinite loop. NOTE: this identifier was SPLIT from CVE-2014-6272 per ADT3 due to different affected versions.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2015-6525",
"description": "Multiple integer overflows in the evbuffer API in Libevent 2.0.x before 2.0.22 and 2.1.x before 2.1.5-beta allow context-dependent attackers to cause a denial of service or possibly have other unspecified impact via \"insanely large inputs\" to the (1) evbuffer_add, (2) evbuffer_prepend, (3) evbuffer_expand, (4) exbuffer_reserve_space, or (5) evbuffer_read function, which triggers a heap-based buffer overflow or an infinite loop. NOTE: this identifier was SPLIT from CVE-2014-6272 per ADT3 due to different affected versions.",
"id": "GSD-2015-6525",
"references": [
"https://www.suse.com/security/cve/CVE-2015-6525.html",
"https://www.debian.org/security/2015/dsa-3119"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
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],
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"id": "GSD-2015-6525",
"modified": "2023-12-13T01:20:04.220542Z",
"schema_version": "1.4.0"
}
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"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 7.5,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:L/Au:N/C:P/I:P/A:P",
"version": "2.0"
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"severity": "HIGH",
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},
"lastModifiedDate": "2015-08-26T02:56Z",
"publishedDate": "2015-08-24T14:59Z"
}
}
}
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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
| Author | Source | Type | Date | Other |
|---|
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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