CVE-2022-21731 MEDIUM

CVE-2022-21731: Type confusion leading to segfault in Tensorflow

Vendor N/A
Product n/a
Published February 3, 2022
Last update May 5, 2025

CVSS base score

6.5/10
Attack vector Network
Attack complexity Low
Privileges required Low
User interaction None
Confidentiality None
Integrity None

CVSS vector

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

What the vulnerability does

01Description

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.

Key dates

02Disclosure timeline

February 3, 2022 CVE published
May 5, 2025 Record updated