GHSA-27j5-4p9v-pp67 `std::abort` raised from `TensorListReserve`

• PyPI tensorflow: < 2.3.4 → fixed in 2.3.4 • PyPI tensorflow: >= 2.4.0, < 2.4.3 → fixed in 2.4.3 • PyPI tensorflow: >= 2.5.0, < 2.5.1 → fixed in 2.5.1 • PyPI tensorflow-cpu: < 2.3.4 → fixed in 2.3.4 • PyPI tensorflow-cpu: >= 2.4.0, < 2.4.3 → fixed in 2.4.3 • PyPI tensorflow-cpu: >= 2.5.0, < 2.5.1 → fixed in 2.5.1 • PyPI tensorflow-gpu: < 2.3.4 → fixed in 2.3.4 • PyPI tensorflow-gpu: >= 2.4.0, < 2.4.3 → fixed in 2.4.3 • PyPI tensorflow-gpu: >= 2.5.0, < 2.5.1 → fixed in 2.5.1

Impact Providing a negative element to `num_elements` list argument of `tf.raw_ops.TensorListReserve` causes the runtime to abort the process due to reallocating a `std::vector` to have a negative number of elements: ```python import tensorflow as tf tf.raw_ops.TensorListReserve( element_shape = tf.constant([1]), num_elements=tf.constant([-1]), element_dtype = tf.int32) ``` The implementation calls `std::vector.resize()` with the new size controlled by input given by the user, without checking that this input is valid. Patches We have patched the issue in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. For more information Please consult our security guide for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by members of the Aivul Team from Qihoo 360.