CVE-2021-29521

Date: May 14, 2021

TensorFlow is an end-to-end open source platform for machine learning. Specifying a negative dense shape in "tf.raw_ops.SparseCountSparseOutput" results in a segmentation fault being thrown out from the standard library as "std::vector" invariants are broken. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a "BatchedMap<T>" (i.e., "std::vector<absl::flat_hash_map<int64,T>>"(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure. If the "shape" tensor has more than one element, "num_batches" is the first value in "shape". Ensuring that the "dense_shape" argument is a valid tensor shape (that is, all elements are non-negative) solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3.

Language: Python