TensorFlow is an open source platform for machine learning. When `RangeSize` receives values that do not fit into an `int64_t`, it crashes. We have patched the issue in GitHub commit 37e64539cd29fcfb814c4451152a60f5d107b0f0. 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.
The product performs a calculation that can produce an integer overflow or wraparound when the logic assumes that the resulting value will always be larger than the original value. This occurs when an integer value is incremented to a value that is too large to store in the associated representation. When this occurs, the value may become a very small or negative number.
| Link | Tags |
|---|---|
| https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/math_ops.cc | third party advisory |
| https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rh87-q4vg-m45j | third party advisory |
| https://github.com/tensorflow/tensorflow/commit/37e64539cd29fcfb814c4451152a60f5d107b0f0 | third party advisory patch |