Description
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.histogram_fixed_width` 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.
Understanding This Vulnerability
This Common Vulnerabilities and Exposures (CVE) entry provides detailed information about a security vulnerability that has been publicly disclosed. CVEs are standardized identifiers assigned by MITRE Corporation to track and catalog security vulnerabilities across software and hardware products.
The severity rating (MEDIUM) indicates the potential impact of this vulnerability based on the CVSS (Common Vulnerability Scoring System) framework. Higher severity ratings typically indicate vulnerabilities that could lead to more significant security breaches if exploited. Security teams should prioritize remediation efforts based on severity, exploit availability, and the EPSS (Exploit Prediction Scoring System) score, which predicts the likelihood of exploitation in the wild.
If this vulnerability affects products or systems in your infrastructure, we recommend reviewing the affected products section, checking for available patches or updates from vendors, and implementing recommended workarounds or solutions until a permanent fix is available. Organizations should also monitor security advisories and threat intelligence feeds for updates about active exploitation of this vulnerability.