BREW-ANSIBLE@9-CVE-2013-2166 (GHSA-C3XQ-CJ8F-7829)
Vulnerability from osv_homebrew – Published: 2026-08-13 16:35 – Updated: 2026-09-09 23:41 – Source website
VLAI
Summary
Inadequate Encryption Strength in python-keystoneclient
Details
python-keystoneclient version 0.2.3 to 0.2.5 has middleware memcache encryption bypass.
Severity
9.8 (Critical)
References
{
"affected": [
{
"ecosystem_specific": {
"fix": "bump",
"range_state": "fixed",
"resource": "python-keystoneclient",
"resource_purl": "pkg:pypi/python-keystoneclient@5.7.0",
"upstream_fixed_in": "0.3.0"
},
"package": {
"ecosystem": "Homebrew",
"name": "ansible@9",
"purl": "pkg:brew/ansible%409"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "9.13.0_4"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "registry",
"upstream_evidence": [
{
"ecosystem": "PyPI",
"key": "pkg:pypi/python-keystoneclient@5.7.0",
"name": "python-keystoneclient",
"resource": "python-keystoneclient",
"strategy": "registry",
"subject_version": "5.7.0"
}
]
},
"details": "python-keystoneclient version 0.2.3 to 0.2.5 has middleware memcache encryption bypass.",
"id": "BREW-ansible@9-CVE-2013-2166",
"modified": "2026-09-09T23:41:06Z",
"published": "2026-08-13T16:35:23Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2013-2166"
},
{
"type": "WEB",
"url": "https://github.com/openstack/python-keystoneclient/commit/eeefb784f24c37d5f56a421e1ccc911cace9385e"
},
{
"type": "WEB",
"url": "https://access.redhat.com/security/cve/cve-2013-2166"
},
{
"type": "WEB",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2013-2166"
},
{
"type": "WEB",
"url": "https://bugzilla.suse.com/show_bug.cgi?id=CVE-2013-2166"
},
{
"type": "ADVISORY",
"url": "https://github.com/advisories/GHSA-c3xq-cj8f-7829"
},
{
"type": "PACKAGE",
"url": "https://github.com/openstack/python-keystoneclient"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/python-keystoneclient/PYSEC-2019-197.yaml"
},
{
"type": "WEB",
"url": "https://security-tracker.debian.org/tracker/CVE-2013-2166"
},
{
"type": "WEB",
"url": "http://lists.fedoraproject.org/pipermail/package-announce/2013-August/113944.html"
},
{
"type": "WEB",
"url": "http://rhn.redhat.com/errata/RHSA-2013-0992.html"
},
{
"type": "WEB",
"url": "http://www.openwall.com/lists/oss-security/2013/06/19/5"
}
],
"schema_version": "1.7.3",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Inadequate Encryption Strength in python-keystoneclient",
"upstream": [
"GHSA-c3xq-cj8f-7829",
"CVE-2013-2166",
"PYSEC-2019-197"
]
}
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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.
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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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