oesa-2024-1441
Vulnerability from osv_openeuler
Published
2024-04-12 11:06
Modified
2026-08-06 11:06
Summary
libgsasl security update
Details
The library includes support for the SASL framework and at least partial support for the CRAM-MD5, EXTERNAL, GSSAPI, ANONYMOUS, PLAIN, SECURID, DIGEST-MD5, LOGIN, and NTLM mechanisms.
Security Fix(es):
GNU SASL libgsasl server-side read-out-of-bounds with malicious authenticated GSS-API client(CVE-2022-2469)
Severity
8.1 (High)
References
| URL | Type | |
|---|---|---|
{
"affected": [
{
"ecosystem_specific": {
"aarch64": [
"libgsasl-debuginfo-1.8.1-2.oe1.aarch64.rpm",
"libgsasl-devel-1.8.1-2.oe1.aarch64.rpm",
"libgsasl-1.8.1-2.oe1.aarch64.rpm",
"libgsasl-debugsource-1.8.1-2.oe1.aarch64.rpm"
],
"src": [
"libgsasl-1.8.1-2.oe1.src.rpm"
],
"x86_64": [
"libgsasl-devel-1.8.1-2.oe1.x86_64.rpm",
"libgsasl-1.8.1-2.oe1.x86_64.rpm",
"libgsasl-debuginfo-1.8.1-2.oe1.x86_64.rpm",
"libgsasl-debugsource-1.8.1-2.oe1.x86_64.rpm"
]
},
"package": {
"ecosystem": "openEuler:20.03-LTS-SP1",
"name": "libgsasl",
"purl": "pkg:rpm/openEuler/libgsasl\u0026distro=openEuler-20.03-LTS-SP1"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.8.1-2.oe1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"severity": "High"
},
"details": "The library includes support for the SASL framework and at least partial support for the CRAM-MD5, EXTERNAL, GSSAPI, ANONYMOUS, PLAIN, SECURID, DIGEST-MD5, LOGIN, and NTLM mechanisms.\r\n\r\nSecurity Fix(es):\r\n\r\nGNU SASL libgsasl server-side read-out-of-bounds with malicious authenticated GSS-API client(CVE-2022-2469)",
"id": "OESA-2024-1441",
"modified": "2026-08-06T11:06:53Z",
"published": "2024-04-12T11:06:53Z",
"references": [
{
"type": "ADVISORY",
"url": "https://www.openeuler.org/en/security/safety-bulletin/detail.html?id=openEuler-SA-2024-1441"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-2469"
}
],
"schema_version": "1.7.2",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "libgsasl security update",
"upstream": [
"CVE-2022-2469"
]
}
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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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