Segfault in SparseCountSparseOutput

Summary

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.

Timeline

1. May 14, 2021, 7:35 PM UTCCVE published
2. Aug 3, 2024, 10:11 PM UTCRecord last updated

Affected versions

• tensorflow tensorflow

  fixed in 2.3.3; From 2.4.0 · fixed in 2.4.2

• tensorflow-gpuPyPI

  From 2.3.0 · fixed in 2.3.3; From 2.4.0 · fixed in 2.4.2

• tensorflowPyPI

  From 2.3.0 · fixed in 2.3.3

• tensorflowPyPI

  From 2.4.0 · fixed in 2.4.2

• tensorflow-cpuPyPI

  From 2.3.0 · fixed in 2.3.3

• tensorflow-cpuPyPI

  From 2.4.0 · fixed in 2.4.2

• tensorflow-gpuPyPI

  From 2.3.0 · fixed in 2.3.3

• tensorflow-gpuPyPI

  From 2.4.0 · fixed in 2.4.2

• tensorflow-cpuPyPI

  From 2.3.0 · fixed in 2.3.3; From 2.4.0 · fixed in 2.4.2

• tensorflowPyPI

  From 2.3.0 · fixed in 2.3.3; From 2.4.0 · fixed in 2.4.2

References 2