CVE-2022-35996
Floating point exception in `Conv2D` in TensorFlow
Description
TensorFlow is an open source platform for machine learning. If `Conv2D` is given empty `input` and the `filter` and `padding` sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 611d80db29dd7b0cfb755772c69d60ae5bca05f9. 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.
How to fix CVE-2022-35996
To remediate CVE-2022-35996, upgrade the affected package to a fixed version below.
- —upgrade to 2.7.2 or later
- —upgrade to 2.7.2 or later
- —upgrade to 2.7.2 or later
- —upgrade to 2.7.2 or later
Is CVE-2022-35996 being exploited?
Low — EPSS is 0.1%, meaning exploitation activity has not been observed at scale.
Affected packages (4)
- from 0, < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1
- from 0, < 2.7.2
- from 0, < 2.7.2
- from 0, < 2.7.2
CVSS scores
| Source | Version | Severity | Vector |
|---|---|---|---|
| osv | CVSS 3.1 | MEDIUM5.9 | CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H |