Description
TensorFlow is an open source platform for machine learning. The `RaggedRangOp` function takes an argument `limits` that is eventually used to construct a `TensorShape` as an `int64`. If `limits` is a very large float, it can overflow when converted to an `int64`. This triggers an `InvalidArgument` but also throws an abort signal that crashes the program. We have patched the issue in GitHub commit 37cefa91bee4eace55715eeef43720b958a01192. 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 supported range. There are no known workarounds 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.