CVE-2022-35973Improper 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 `QuantizedMatMul` is given nonscalar input for: `min_a`, `max_a`, `min_b`, or `max_b` It gives a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48. 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 suppor

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

📋Vendor Advisories

1
Debian
CVE-2022-35973: tensorflow - TensorFlow is an open source platform for machine learning. If `QuantizedMatMul`...2022
CVE-2022-35973 — Improper Input Validation | cvebase