CVE-2022-36005

TensorFlow is an open source platform for machine learning. When `tf.quantization.fake_quant_with_min_max_vars_gradient` receives input `min` or `max` that is nonscalar, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed. 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: 21%
Affected Products (NVD)
VendorProductVersion
googletensorflow
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