CVE-2022-29211: Segfault in TensorFlow if `tf.histogram_fixed_width` is called with NaN values
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.histogramfixedwidth is vulnerable to a crash when the values array contain Not a Number (NaN) elements. The implementation assumes that all floating point operations are defined and then converts a floating point result to an integer index. If values contains NaN then the result of the division is still NaN and the cast to int32 would result in a crash. This only occurs on the CPU implementation. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Affected Software
Remediation
Patch Available
Event History
Frequently Asked Questions
What is the severity of CVE-2022-29211?
CVE-2022-29211 has a medium-severity rating as it allows a crash due to processing of NaN values.
How do I fix CVE-2022-29211?
To fix CVE-2022-29211, upgrade to TensorFlow versions 2.9.0, 2.8.1, 2.7.2, or 2.6.4 or later.
Which versions of TensorFlow are affected by CVE-2022-29211?
CVE-2022-29211 affects TensorFlow versions prior to 2.9.0, 2.8.1, 2.7.2, and 2.6.4.
What causes the vulnerability in CVE-2022-29211?
The vulnerability in CVE-2022-29211 is caused by the `tf.histogram_fixed_width` function not handling NaN elements in the values array.
Is CVE-2022-29211 exploitable remotely?
CVE-2022-29211 is not classified as a remote exploit since it requires manipulating the input data to trigger the crash.