Vulnerability Monitor

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CVE-2021-39207

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.

Security Impact Summary

This vulnerability carries a HIGH severity rating with a CVSS v3.1 score of 8.4, indicating it can be exploited remotely over the network but requires specific conditions to be met without requiring user interaction requiring only low-level privileges . The vulnerability impacts confidentiality (data exposure), integrity (unauthorized modifications), and limited availability for affected systems. Impacting 1 product from facebook organizations running these solutions should prioritize assessment and patching.

Historical Context

Reported in 2021, this vulnerability emerged during an era marked by increased sophistication in supply chain attacks, cloud infrastructure vulnerabilities, and software-as-a-service (SaaS) security challenges. Security practices during this period emphasized zero-trust architectures, container security, and API protection.

Published

2021-09-10T23:15:07.343

Last Modified

2024-11-21T06:18:54.097

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 8.4 (HIGH)

CVSSv2 Vector

AV:N/AC:L/Au:S/C:P/I:P/A:P

Access Vector: NETWORK
Access Complexity: LOW
Authentication: SINGLE
Confidentiality Impact: PARTIAL
Integrity Impact: PARTIAL
Availability Impact: PARTIAL

Exploitability Score

8.0

Impact Score

6.4

Weaknesses

Type: Secondary
CWE-502

Affected Vendors & Products

Type	Vendor	Product	Version/Range	Vulnerable?
Application	facebook	parlai	< 1.1.0	Yes

References

https://github.com/facebookresearch/ParlAI/commit/4374fa2aba383db6526ab36e939eb1cf8ef99879 Patch, Third Party Advisory ([email protected])
https://github.com/facebookresearch/ParlAI/commit/507d066ef432ea27d3e201da08009872a2f37725 Patch, Third Party Advisory ([email protected])
https://github.com/facebookresearch/ParlAI/security/advisories/GHSA-m87f-9fvv-2mgg Patch, Third Party Advisory ([email protected])
https://github.com/facebookresearch/ParlAI/commit/4374fa2aba383db6526ab36e939eb1cf8ef99879 Patch, Third Party Advisory (af854a3a-2127-422b-91ae-364da2661108)
https://github.com/facebookresearch/ParlAI/commit/507d066ef432ea27d3e201da08009872a2f37725 Patch, Third Party Advisory (af854a3a-2127-422b-91ae-364da2661108)
https://github.com/facebookresearch/ParlAI/security/advisories/GHSA-m87f-9fvv-2mgg Patch, Third Party Advisory (af854a3a-2127-422b-91ae-364da2661108)

How SecUtils Interprets This CVE

SecUtils normalizes and enriches National Vulnerability Database (NVD) records by standardizing vendor and product identifiers, aggregating vulnerability metadata from both NVD and MITRE sources, and providing structured context for security teams. For facebook's affected products, we extract Common Platform Enumeration (CPE) data, Common Weakness Enumeration (CWE) classifications, CVSS severity metrics, and reference data to enable rapid vulnerability prioritization and asset correlation. This record contains no exploit code, proof-of-concept instructions, or attack methodologies—only defensive intelligence necessary for patch management, risk assessment, and security operations.