BREW-PERL-DBD-MYSQL-CVE-… (CVE-2016-1251)
Vulnerability from osv_homebrew – Published: 2026-08-13 17:25 – Updated: 2026-08-13 17:25 – Source website
VLAI
Details
There is a vulnerability of type use-after-free affecting DBD::mysql (aka DBD-mysql or the Database Interface (DBI) MySQL driver for Perl) 3.x and 4.x before 4.041 when used with mysql_server_prepare=1.
Severity
8.1 (High)
References
{
"affected": [
{
"ecosystem_specific": {
"fix": "bump",
"range_state": "fixed",
"upstream_fixed_in": "4.041"
},
"package": {
"ecosystem": "Homebrew",
"name": "perl-dbd-mysql",
"purl": "pkg:brew/perl-dbd-mysql"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "5.013_2"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "git",
"upstream_evidence": [
{
"ecosystem": "GIT",
"key": "https://github.com/perl5-dbi/dbd-mysql",
"name": "https://github.com/perl5-dbi/dbd-mysql",
"strategy": "git",
"subject_version": "5.013"
},
{
"ecosystem": "CPAN",
"key": "pkg:cpan/DVEEDEN/DBD-mysql@5.013",
"name": "DBD-mysql",
"strategy": "cpansa",
"subject_version": "5.013"
}
]
},
"details": "There is a vulnerability of type use-after-free affecting DBD::mysql (aka DBD-mysql or the Database Interface (DBI) MySQL driver for Perl) 3.x and 4.x before 4.041 when used with mysql_server_prepare=1.",
"id": "BREW-perl-dbd-mysql-CVE-2016-1251",
"modified": "2026-08-13T17:25:54Z",
"published": "2026-08-13T17:25:54Z",
"references": [
{
"type": "ADVISORY",
"url": "http://www.openwall.com/lists/oss-security/2016/11/28/2"
},
{
"type": "ADVISORY",
"url": "http://www.securityfocus.com/bid/94573"
},
{
"type": "ADVISORY",
"url": "https://security.gentoo.org/glsa/201701-51"
},
{
"type": "ADVISORY",
"url": "https://tracker.debian.org/news/819888"
},
{
"type": "FIX",
"url": "https://anonscm.debian.org/cgit/pkg-perl/packages/libdbd-mysql-perl.git/commit/?id=a8b97e4713391b1f8beffbfddac483c276feaff1"
},
{
"type": "FIX",
"url": "https://github.com/perl5-dbi/DBD-mysql/commit/3619c170461a3107a258d1fd2d00ed4832adb1b1"
}
],
"schema_version": "1.7.3",
"severity": [
{
"score": "CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
],
"upstream": [
"CVE-2016-1251"
]
}
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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
- 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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