CVE-2022-23573

Description

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.

How to fix CVE-2022-23573

To remediate CVE-2022-23573, upgrade the affected package to a fixed version below.

• —upgrade to 2.5.3 or later
• —upgrade to 2.5.3 or later
• —upgrade to 2.5.3 or later
• —upgrade to ef1d027be116f25e25bb94a60da491c2cf55bd0b or later
• —upgrade to 2.5.3 or later
• —upgrade to ef1d027be116f25e25bb94a60da491c2cf55bd0b or later

Is CVE-2022-23573 being exploited?

Low — EPSS is 0.3%, meaning exploitation activity has not been observed at scale.

Affected packages (6)

• from 0, < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1
• from 0, < 2.5.3
• from 0, < 2.5.3
• from 0, < ef1d027be116f25e25bb94a60da491c2cf55bd0b | from 0, < 2.5.3, >= 2.6.0, < 2.6.3
• from 0, < 2.5.3
• from 0, < ef1d027be116f25e25bb94a60da491c2cf55bd0b | from 0, < 2.5.3, >= 2.6.0, < 2.6.3

CVSS scores

References (7)

• ADVISORYnvd.nist.gov/vuln/detail/CVE-2022-23573
• WEBgithub.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-82.yaml
• WEBgithub.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-137.yaml
• WEBgithub.com/tensorflow/tensorflow