Vulnerability in Google Tensorflow
CVE-2022-35996
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.
EPSS: 0.004 (33.7th percentile) — read the EPSS interpretation.
CVSS v3 metric
CVSS v3 base score 5.9 (Medium). Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H.
Affected products
- Google Tensorflow — versions 2.10
- Tensorflow — versions < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1
Weakness classification (CWE)
References
- security-advisories@github.com (x_refsource_CONFIRM, Third Party Advisory)
- security-advisories@github.com (Patch, Third Party Advisory, x_refsource_MISC)
Frequently asked questions
- What is CVE-2022-35996?
- CVE-2022-35996 is a medium-severity vulnerability in Google Tensorflow, classified under Divide By Zero. CVSS score: 5.9/10. Published 2022-09-16.
- How severe is CVE-2022-35996?
- Medium severity. CVSS v3 base score is 5.9 out of 10.