Vulnerability in Google Tensorflow

CVE-2022-21731

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.

EPSS: 0.008 (54.3th percentile) — read the EPSS interpretation.

CVSS v3 metric

CVSS v3 base score 6.5 (Medium). Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H.

Affected products

Weakness classification (CWE)

References

Frequently asked questions

What is CVE-2022-21731?
CVE-2022-21731 is a medium-severity vulnerability in Google Tensorflow, classified under Access of Resource Using Incompatible Type (Type Confusion). CVSS score: 6.5/10. Published 2022-02-03.
How severe is CVE-2022-21731?
Medium severity. CVSS v3 base score is 6.5 out of 10.