Vulnerability in Google Tensorflow

CVE-2022-23573

Tensorflow is an Open Source Machine Learning Framework. The implementation of `AssignOp` can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Published · last modified .

CVSS v3 metric

CVSS v3 base score 7.6 (High). Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H.

EPSS exploit prediction

EPSS: 0.008 (53.7th percentile), scored .

Very low probability of exploitation in the next 30 days; routine patching cadence is appropriate. 54th percentile — 53.7% of CVEs in the catalogue have a lower EPSS than this one. How to read EPSS.

EPSS trend (30 days)EPSS over the last 30 days for CVE-2022-23573: held from 0.008 to 0.008.

EPSS over last 30 days · oldest: 0.008 · newest: 0.008 · change: +0.000

Affected products

Weakness classification (CWE)

Public proof-of-concept exploits

References

Frequently asked questions

What is CVE-2022-23573?
CVE-2022-23573 is a high-severity vulnerability in Google Tensorflow, classified under Use of Uninitialized Resource. CVSS score: 7.6/10. Published 2022-02-04.
How severe is CVE-2022-23573?
High severity. CVSS v3 base score is 7.6 out of 10.
Is CVE-2022-23573 known to be exploited?
1 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.