BREW-ANIMDL-CVE-2020-14343 (GHSA-8Q59-Q68H-6HV4)
Vulnerability from osv_homebrew – Published: 2026-08-13 16:35 – Updated: 2026-09-09 23:40 – Source websiteA vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
{
"affected": [
{
"ecosystem_specific": {
"fix": "bump",
"range_state": "fixed",
"resource": "pyyaml",
"resource_purl": "pkg:pypi/pyyaml@6.0.3",
"upstream_fixed_in": "5.4"
},
"package": {
"ecosystem": "Homebrew",
"name": "animdl",
"purl": "pkg:brew/animdl"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.7.27_5"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "registry",
"upstream_evidence": [
{
"ecosystem": "PyPI",
"key": "pkg:pypi/pyyaml@6.0.3",
"name": "pyyaml",
"resource": "pyyaml",
"strategy": "registry",
"subject_version": "6.0.3"
}
]
},
"details": "A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.",
"id": "BREW-animdl-CVE-2020-14343",
"modified": "2026-09-09T23:40:59Z",
"published": "2026-08-13T16:35:16Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2020-14343"
},
{
"type": "WEB",
"url": "https://github.com/SeldonIO/seldon-core/issues/2252"
},
{
"type": "WEB",
"url": "https://github.com/yaml/pyyaml/issues/420"
},
{
"type": "WEB",
"url": "https://github.com/yaml/pyyaml/issues/420#issuecomment-663673966"
},
{
"type": "WEB",
"url": "https://github.com/yaml/pyyaml/commit/a001f2782501ad2d24986959f0239a354675f9dc"
},
{
"type": "WEB",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=1860466"
},
{
"type": "ADVISORY",
"url": "https://github.com/advisories/GHSA-8q59-q68h-6hv4"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/pyyaml/PYSEC-2021-142.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/yaml/pyyaml"
},
{
"type": "WEB",
"url": "https://pypi.org/project/PyYAML"
},
{
"type": "WEB",
"url": "https://www.oracle.com/security-alerts/cpuapr2022.html"
},
{
"type": "WEB",
"url": "https://www.oracle.com/security-alerts/cpujul2022.html"
}
],
"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": "Improper Input Validation in PyYAML",
"upstream": [
"GHSA-8q59-q68h-6hv4",
"CVE-2020-14343",
"PYSEC-2021-142"
]
}
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.
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.
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.