CVE-2022-23594
Published: 04 February 2022
Summary
CVE-2022-23594 is a high-severity Out-of-bounds Read (CWE-125) vulnerability in Google Tensorflow. Its CVSS base score is 8.8 (High).
Operationally, ranked at the 5.1th percentile by exploit likelihood (below the median); 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-2022-0947
Vulnerability details
Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow (MLIR) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these…
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assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered.
- 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
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.
Out-of-bounds writes that corrupt control flow or inject shellcode are rendered non-executable by the same memory protections.