BREW-IPYTHON-CVE-2019-12760 (PYSEC-2019-109)
Vulnerability from osv_homebrew – Published: 2026-08-13 17:00 – Updated: 2026-09-17 17:44 – Source website
VLAI
Details
** DISPUTED ** A deserialization vulnerability exists in the way parso through 0.4.0 handles grammar parsing from the cache. Cache loading relies on pickle and, provided that an evil pickle can be written to a cache grammar file and that its parsing can be triggered, this flaw leads to Arbitrary Code Execution. NOTE: This is disputed because "the cache directory is not under control of the attacker in any common configuration."
References
{
"affected": [
{
"ecosystem_specific": {
"fix": "bump",
"range_state": "fixed",
"resource": "parso",
"resource_purl": "pkg:pypi/parso@0.8.7",
"upstream_fixed_in": "0.5.0"
},
"package": {
"ecosystem": "Homebrew",
"name": "ipython",
"purl": "pkg:brew/ipython"
},
"ranges": [
{
"events": [
{
"introduced": "6.2.1"
},
{
"fixed": "7.6.1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "registry",
"upstream_evidence": [
{
"ecosystem": "PyPI",
"key": "pkg:pypi/parso@0.8.7",
"name": "parso",
"resource": "parso",
"strategy": "registry",
"subject_version": "0.8.7"
}
]
},
"details": "** DISPUTED ** A deserialization vulnerability exists in the way parso through 0.4.0 handles grammar parsing from the cache. Cache loading relies on pickle and, provided that an evil pickle can be written to a cache grammar file and that its parsing can be triggered, this flaw leads to Arbitrary Code Execution. NOTE: This is disputed because \"the cache directory is not under control of the attacker in any common configuration.\"",
"id": "BREW-ipython-CVE-2019-12760",
"modified": "2026-09-17T17:44:50Z",
"published": "2026-08-13T17:00:01Z",
"references": [
{
"type": "WEB",
"url": "https://gist.github.com/dhondta/f71ae7e5c4234f8edfd2f12503a5dcc7"
},
{
"type": "REPORT",
"url": "https://github.com/davidhalter/parso/issues/75"
},
{
"type": "ADVISORY",
"url": "https://github.com/advisories/GHSA-22mf-97vh-x8rw"
}
],
"schema_version": "1.7.3",
"upstream": [
"PYSEC-2019-109",
"CVE-2019-12760",
"GHSA-22mf-97vh-x8rw"
]
}
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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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