CVE-2022-35967

TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` 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 49b3824d83af706df0ad07e4e677d88659756d89. 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.
ProviderTypeBase ScoreAtk. VectorAtk. ComplexityPriv. RequiredVector
GitHub_MCNA
5.9 MEDIUM
NETWORK
HIGH
NONE
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Base Score
CVSS 3.x
EPSS Score
Percentile: 20%
Affected Products (NVD)
VendorProductVersion
googletensorflow
2.7.0 ≤
𝑥
< 2.7.2
googletensorflow
2.8.0 ≤
𝑥
< 2.8.1
googletensorflow
2.9.0 ≤
𝑥
< 2.9.1
googletensorflow
2.10:rc0
googletensorflow
2.10:rc1
googletensorflow
2.10:rc2
googletensorflow
2.10:rc3
𝑥
= Vulnerable software versions
Early Detection
Affected products identified ahead of NVD analysis through intelligence sources.
VendorProductVersionSource
tensorflowtensorflow
𝑥
< 2.7.2
CNA