CVE-2022-35974Improper Input Validation in Tensorflow

Severity
7.5HIGHNVD
CNA5.9
EPSS
0.1%
top 80.05%
CISA KEV
Not in KEV
Exploit
No known exploits
Timeline
PublishedSep 16

Description

TensorFlow is an open source platform for machine learning. If `QuantizeDownAndShrinkRange` is given nonscalar inputs for `input_min` or `input_max`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 73ad1815ebcfeb7c051f9c2f7ab5024380ca8613. 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

CVSS vector

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:HExploitability: 3.9 | Impact: 3.6

Affected Packages3 packages

NVDgoogle/tensorflow2.7.02.7.2+3
CVEListV5tensorflow/tensorflow< 2.7.2+2
PyPIintel/optimization_for_tensorflow2.8.02.8.1+2

Patches

🔴Vulnerability Details

3
CVEList
Segfault in `QuantizeDownAndShrinkRange` in TensorFlow2022-09-16
OSV
TensorFlow vulnerable to segfault in `QuantizeDownAndShrinkRange`2022-09-16
GHSA
TensorFlow vulnerable to segfault in `QuantizeDownAndShrinkRange`2022-09-16

📋Vendor Advisories

1
Debian
CVE-2022-35974: tensorflow - TensorFlow is an open source platform for machine learning. If `QuantizeDownAndS...2022
CVE-2022-35974 — Improper Input Validation | cvebase