Vulnerability Description
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 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.
CVSS Score
HIGH
Affected Products
| Vendor | Product | Versions |
|---|---|---|
| Tensorflow | 2.7.0 |
Related Weaknesses (CWE)
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9x52-887g-fhc2Third Party Advisory
- https://github.com/tensorflow/tensorflow/tree/274df9b02330b790aa8de1cee164b70f72Third Party Advisory
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9x52-887g-fhc2Third Party Advisory
- https://github.com/tensorflow/tensorflow/tree/274df9b02330b790aa8de1cee164b70f72Third Party Advisory
FAQ
What is CVE-2022-23594?
CVE-2022-23594 is a vulnerability with a CVSS score of 8.8 (HIGH). 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...
How severe is CVE-2022-23594?
CVE-2022-23594 has been rated HIGH with a CVSS base score of 8.8/10. Review the CVSS metrics above for detailed severity breakdown.
Is there a patch for CVE-2022-23594?
Check the references section above for vendor advisories and patch information. Affected products include: Google Tensorflow.