CVE-2022-35999: `CHECK` fail in `Conv2DBackpropInput` in TensorFlow
TensorFlow is an open source platform for machine learning. When Conv2DBackpropInput receives empty outbackprop inputs (e.g. [3, 1, 0, 1]), the current CPU/GPU kernels CHECK fail (one with dnnl, the other with cudnn). This can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 27a65a43cf763897fecfa5cdb5cc653fc5dd0346. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Affected Software
Remediation
Event History
Frequently Asked Questions
What is the severity of CVE-2022-35999?
CVE-2022-35999 is classified as a denial of service vulnerability that can lead to application crashes.
How do I fix CVE-2022-35999?
To remediate CVE-2022-35999, upgrade TensorFlow to a version that is not vulnerable, specifically versions later than 2.10-rc3.
What versions of TensorFlow are affected by CVE-2022-35999?
CVE-2022-35999 affects TensorFlow versions up to 2.10-rc3, including versions 2.7.2, 2.8.0, and 2.9.0 through 2.9.1.
What components of TensorFlow are impacted by CVE-2022-35999?
CVE-2022-35999 affects the Conv2DBackpropInput operation within TensorFlow when it receives empty out_backprop inputs.
Can CVE-2022-35999 be exploited remotely?
Yes, CVE-2022-35999 can be exploited remotely to trigger a denial of service condition.