CVE-2022-21731

Public Exploit
Type confusion leading to segfault in Tensorflow

Description

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ConcatV2` can be used to trigger a denial of service attack via a segfault caused by a type confusion. The `axis` argument is translated into `concat_dim` in the `ConcatShapeHelper` helper function. Then, a value for `min_rank` is computed based on `concat_dim`. This is then used to validate that the `values` tensor has at least the required rank. However, `WithRankAtLeast` receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that `min_rank` is a 32-bits value and the value of `axis`, the `rank` argument is a negative value, so the error check is bypassed. 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

6.5
CVSS
Severity: Medium
CVSS 3.1 •
CVSS 2.0 •
EPSS 0.29%
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-2022-21731?
CVE-2022-21731 has been scored as a medium severity vulnerability.
How to fix CVE-2022-21731?
To fix CVE-2022-21731, 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-2022-21731 being actively exploited in the wild?
It is possible that CVE-2022-21731 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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