CVE-2022-35970: Segfault in `QuantizedInstanceNorm` in TensorFlow
Affected: tensorflow · Exploitation: unlikely (under 1%)
Not in CyberSIXT coverage yet: no article names this CVE. This page shows the public record.
Higher than 44% of scored CVEs
DescriptionCVE.org
TensorFlow is an open source platform for machine learning. If `QuantizedInstanceNorm` is given `x_min` or `x_max` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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 products1
From the CVE record. A product or version that is not listed is unknown, not unaffected.
- tensorflow · tensorflow< 2.7.2; >= 2.8.0, < 2.8.1; >= 2.9.0, < 2.9.1
On the Atlas
Every published CVE is on the CyberSIXT Atlas, grouped by weakness, vendor and month.
- Exploitation
- Unlikely (under 1%). EPSS under 1%, or no score yet.
- CISA KEV
- Not listed
- Public check
- No public nuclei template
- Vendor
- tensorflow
- Published
- September 2022
CoverageNo articles yet
No CyberSIXT article names CVE-2022-35970 yet, so there is no coverage timeline, action brief or change log for it. Everything on this page comes from the public CVE record, CISA KEV, EPSS and the nuclei template index. Search the archive or see the CVEs in the news.