CVE-2022-21726

Public Exploit
Out of bounds read in Tensorflow

Description

Tensorflow is an Open Source Machine Learning Framework. The implementation of `Dequantize` does not fully validate the value of `axis` and can result in heap OOB accesses. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Category

8.1
CVSS
Severity: High
CVSS 3.1 •
CVSS 2.0 •
EPSS 0.28%
Third-Party Advisory github.com Third-Party Advisory github.com Third-Party Advisory github.com
Affected: n/a n/a
Published at:
Updated at:

References

Frequently Asked Questions

What is the severity of CVE-2022-21726?
CVE-2022-21726 has been scored as a high severity vulnerability.
How to fix CVE-2022-21726?
To fix CVE-2022-21726, 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-2022-21726 being actively exploited in the wild?
It is possible that CVE-2022-21726 is being exploited or will be exploited in a near future based on public information. According to its EPSS score, there is a ~0% probability that this vulnerability will be exploited by malicious actors in the next 30 days.
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