Integer Overflow or Wraparound
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. The fix will be included in TensorFlow 2.10.0. This vulnerability was also fixed in TensorFlow 2.9.2, TensorFlow 2.8.3, and TensorFlow 2.7.4, as these are also affected and still in supported range. There are no known workarounds for this issue. This issue affects versions prior to 2.7.4, 2.8.x prior to 2.8.3, and 2.9.x prior to 2.9.2.
CWE-190 - Integer Overflow or Wraparound
The software 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 can introduce other weaknesses when the calculation is used for resource management or execution control.