CVE-2022-23594

Out of bounds read in Tensorflow

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.

Category

8.8
CVSS
Severity: High
CVSS 3.1 •
CVSS 2.0 •
EPSS 0.02%
Third-Party Advisory github.com Third-Party Advisory github.com
Affected: tensorflow tensorflow
Published at:
Updated at:

References

Link Tags
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9x52-887g-fhc2 third party advisory
https://github.com/tensorflow/tensorflow/tree/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/core/ir/importexport third party advisory

Frequently Asked Questions

What is the severity of CVE-2022-23594?
CVE-2022-23594 has been scored as a high severity vulnerability.
How to fix CVE-2022-23594?
To fix CVE-2022-23594, make sure you are using an up-to-date version of the affected component(s) by checking the vendor release notes. As for now, there are no other specific guidelines available.
Is CVE-2022-23594 being actively exploited in the wild?
As for now, there are no information to confirm that CVE-2022-23594 is being actively exploited. According to its EPSS score, there is a ~0% probability that this vulnerability will be exploited by malicious actors in the next 30 days.
What software or system is affected by CVE-2022-23594?
CVE-2022-23594 affects tensorflow tensorflow.
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