BREW-HARLEQUIN-CVE-2020-13091 (PYSEC-2020-73)
Vulnerability from osv_homebrew – Published: 2026-08-13 16:55 – Updated: 2026-08-13 16:55 – Source website
VLAI
Details
** DISPUTED ** pandas through 1.0.3 can unserialize and execute commands from an untrusted file that is passed to the read_pickle() function, if reduce makes an os.system call. NOTE: third parties dispute this issue because the read_pickle() function is documented as unsafe and it is the user's responsibility to use the function in a secure manner.
References
{
"affected": [
{
"ecosystem_specific": {
"fix": "bump",
"range_state": "fixed",
"resource": "pandas",
"resource_purl": "pkg:pypi/pandas@3.0.5",
"upstream_fixed_in": "1.0.4"
},
"package": {
"ecosystem": "Homebrew",
"name": "harlequin",
"purl": "pkg:brew/harlequin"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.8.1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "registry",
"upstream_evidence": [
{
"ecosystem": "PyPI",
"key": "pkg:pypi/pandas@3.0.5",
"name": "pandas",
"resource": "pandas",
"strategy": "registry",
"subject_version": "3.0.5"
}
]
},
"details": "** DISPUTED ** pandas through 1.0.3 can unserialize and execute commands from an untrusted file that is passed to the read_pickle() function, if __reduce__ makes an os.system call. NOTE: third parties dispute this issue because the read_pickle() function is documented as unsafe and it is the user\u0027s responsibility to use the function in a secure manner.",
"id": "BREW-harlequin-CVE-2020-13091",
"modified": "2026-08-13T16:55:40Z",
"published": "2026-08-13T16:55:40Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/0FuzzingQ/vuln/blob/master/pandas%20unserialize.md"
},
{
"type": "WEB",
"url": "https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_pickle.html"
}
],
"schema_version": "1.7.3",
"upstream": [
"PYSEC-2020-73",
"CVE-2020-13091"
]
}
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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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