CVE-2022-35966

TensorFlow is an open source platform for machine learning. If `QuantizedAvgPool` 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 7cdf9d4d2083b739ec81cfdace546b0c99f50622. 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: 19%
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
Common Weakness Enumeration
References
https://github.com/tensorflow/tensorflow/commit/7cdf9d4d2083b739ec81cfdace546b0c99f50622
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4w68-4x85-mjj9
https://github.com/tensorflow/tensorflow/commit/7cdf9d4d2083b739ec81cfdace546b0c99f50622
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4w68-4x85-mjj9