PYSEC-2021-334
Vulnerability from pysec - Published: 2021-09-10 23:15 - Updated: 2021-09-23 16:57parlai is a framework for training and evaluating AI models on a variety of openly available dialogue datasets. In affected versions the package is vulnerable to YAML deserialization attack caused by unsafe loading which leads to Arbitary code execution. This security bug is patched by avoiding unsafe loader users should update to version above v1.1.0. If upgrading is not possible then users can change the Loader used to SafeLoader as a workaround. See commit 507d066ef432ea27d3e201da08009872a2f37725 for details.
| Name | purl | parlai | pkg:pypi/parlai |
|---|
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "parlai",
"purl": "pkg:pypi/parlai"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "507d066ef432ea27d3e201da08009872a2f37725"
},
{
"fixed": "4374fa2aba383db6526ab36e939eb1cf8ef99879"
}
],
"repo": "https://github.com/facebookresearch/ParlAI",
"type": "GIT"
},
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.1.0"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"0.1.20200409",
"0.1.20200416",
"0.1.20200610",
"0.1.20200713",
"0.1.20200716",
"0.10.0",
"0.8.0",
"0.9.0",
"0.9.1",
"0.9.2",
"0.9.3",
"0.9.4",
"1.0.0"
]
}
],
"aliases": [
"CVE-2021-39207",
"GHSA-m87f-9fvv-2mgg"
],
"details": "parlai is a framework for training and evaluating AI models on a variety of openly available dialogue datasets. In affected versions the package is vulnerable to YAML deserialization attack caused by unsafe loading which leads to Arbitary code execution. This security bug is patched by avoiding unsafe loader users should update to version above v1.1.0. If upgrading is not possible then users can change the Loader used to SafeLoader as a workaround. See commit 507d066ef432ea27d3e201da08009872a2f37725 for details.",
"id": "PYSEC-2021-334",
"modified": "2021-09-23T16:57:40.954858Z",
"published": "2021-09-10T23:15:00Z",
"references": [
{
"type": "FIX",
"url": "https://github.com/facebookresearch/ParlAI/commit/507d066ef432ea27d3e201da08009872a2f37725"
},
{
"type": "FIX",
"url": "https://github.com/facebookresearch/ParlAI/commit/4374fa2aba383db6526ab36e939eb1cf8ef99879"
},
{
"type": "ADVISORY",
"url": "https://github.com/facebookresearch/ParlAI/security/advisories/GHSA-m87f-9fvv-2mgg"
}
]
}
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.