CVE-2022-21728

Public Exploit
Out of bounds read in Tensorflow

Description

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ReverseSequence` does not fully validate the value of `batch_dim` and can result in a heap OOB read. There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of `Dim` would access elements before the start of an array. 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 1.07% Top 25%
Third-Party Advisory github.com 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-2022-21728?
CVE-2022-21728 has been scored as a high severity vulnerability.
How to fix CVE-2022-21728?
To fix CVE-2022-21728, 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-2022-21728 being actively exploited in the wild?
It is possible that CVE-2022-21728 is being exploited or will be exploited in a near future based on public information. According to its EPSS score, there is a ~1% probability that this vulnerability will be exploited by malicious actors in the next 30 days.
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