CVE intelligence and bounded remediation
CVE-2021-39207 — parlai is a framework for training and evaluating AI models on a variety of openly available dialogue datasets
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.
- Severity
- High
- CVSS
- 8.8 (3.1)
- Published
- 2021-09-10
- CISA KEV
- Not currently listed
- Ecosystem
- software/application
- Weaknesses
- CWE-502
Affected products
- facebook / parlai
Matched remediation archetype
Unsafe deserialization and object reconstruction
This catalog composition supplies bounded fallback guidance. Explicitly reviewed curated workflows load with the complete record below.
Check exposure
- Inventory serialization formats accepted from requests, queues, caches, files, cookies, and cross-service messages.
- Trace whether untrusted input can select classes, types, callbacks, constructors, or object hooks during decoding.
- Identify signing, schema validation, trust-boundary, and compatibility settings for each decoder.
Remediate safely
- Replace native object deserialization with a data-only format and explicit schema validation.
- If replacement is not immediate, use a safe decoder with a minimal type allowlist and disable polymorphic or executable hooks.
- Update the affected library and add inert tests for unknown types, extra fields, malformed nesting, and unsigned data.
Authoritative sources
Complete CVE record and remediation plan
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