While calculating the size of the output within the tf.range
kernel, there is a conditional statement of type int64 = condition ? int64 : double
. Due to C++ implicit conversion rules, both branches of the condition will be cast to double
and the result would be truncated before the assignment. This result in overflows:
import tensorflow as tf
tf.sparse.eye(num_rows=9223372036854775807, num_columns=None)
Similarly, tf.range
would result in crashes due to overflows if the start or end point are too large.
import tensorflow as tf
tf.range(start=-1e+38, limit=1)
We have patched the issue in GitHub commits 6d94002a09711d297dbba90390d5482b76113899 (merging #51359) and 1b0e0ec27e7895b9985076eab32445026ae5ca94 (merging #51711).
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
This vulnerability has been reported externally via GitHub issue, GitHub issue and GitHub issue.
{ "nvd_published_at": "2021-11-05T22:15:00Z", "cwe_ids": [ "CWE-681" ], "severity": "MODERATE", "github_reviewed": true, "github_reviewed_at": "2021-11-08T22:47:54Z" }