CVE-2022-41901
Published: 18 November 2022
Summary
CVE-2022-41901 is a medium-severity Improper Input Validation (CWE-20) vulnerability in Google Tensorflow. Its CVSS base score is 4.8 (Medium).
Operationally, ranked in the top 47.7% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as Deep Learning Frameworks.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-7345
Vulnerability details
TensorFlow is an open source platform for machine learning. An input `sparse_matrix` that is not a matrix with a shape with rank 0 will trigger a `CHECK` fail in `tf.raw_ops.SparseMatrixNNZ`. We have patched the issue in GitHub commit f856d02e5322821aad155dad9b3acab1e9f5d693. The…
more
fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
- 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: tensorflow, machine learning, tensorflow, tensorflow, tensorflow
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.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Directly implements checks on information inputs to reject invalid data before processing.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.