CVE-2021-43811
Published: 08 December 2021
Summary
CVE-2021-43811 is a high-severity Code Injection (CWE-94) vulnerability in Amazon Sockeye. Its CVSS base score is 7.8 (High).
Operationally, ranked in the top 7.3% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as Deep Learning Frameworks.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2021-0247
Vulnerability details
Sockeye is an open-source sequence-to-sequence framework for Neural Machine Translation built on PyTorch. Sockeye uses YAML to store model and data configurations on disk. Versions below 2.3.24 use unsafe YAML loading, which can be made to execute arbitrary code embedded…
more
in config files. An attacker can add malicious code to the config file of a trained model and attempt to convince users to download and run it. If users run the model, the embedded code will run locally. The issue is fixed in version 2.3.24.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Deep Learning Frameworks
- Risk Domain
- N/A
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: pytorch
Related Threats
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Makes persistent code injection into loaded programs impossible when the executable image itself resides on hardware-protected read-only media.
Dynamically generated code can be produced and executed inside the isolated chamber, preventing host compromise from code-injection payloads.
Validates inputs used in dynamic code generation to block injected directives.
Directly prevents execution of attacker-supplied code written into data memory regions.