Heap OOB in `RaggedGather` in TensorFlow

Summary

TensorFlow is an end-to-end open source platform for machine learning. In affected versions if the arguments to `tf.raw_ops.RaggedGather` don't determine a valid ragged tensor code can trigger a read from outside of bounds of heap allocated buffers. The implementation directly reads the first dimension of a tensor shape before checking that said tensor has rank of at least 1 (i.e., it is not a scalar). Furthermore, the implementation does not check that the list given by `params_nested_splits` is not an empty list of tensors. We have patched the issue in GitHub commit a2b743f6017d7b97af1fe49087ae15f0ac634373. 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.

Timeline

1. Aug 12, 2021, 8:30 PM UTCCVE published
2. Aug 4, 2024, 1:23 AM UTCRecord last updated

Affected versions

• tensorflow tensorflow

  From 2.5.0 · fixed in 2.5.1; From 2.4.0 · fixed in 2.4.3; fixed in 2.3.4

• tensorflowPyPI

  From 2.3.0 · fixed in 2.3.4; From 2.4.0 · fixed in 2.4.3

• tensorflowPyPI

  fixed in 2.3.4

• tensorflowPyPI

  From 2.4.0 · fixed in 2.4.3

• tensorflowPyPI

  From 2.5.0 · fixed in 2.5.1

• tensorflow-cpuPyPI

  fixed in 2.3.4

• tensorflow-cpuPyPI

  From 2.4.0 · fixed in 2.4.3

• tensorflow-cpuPyPI

  From 2.5.0 · fixed in 2.5.1

• tensorflow-gpuPyPI

  fixed in 2.3.4

• tensorflow-gpuPyPI

  From 2.4.0 · fixed in 2.4.3

• tensorflow-gpuPyPI

  From 2.5.0 · fixed in 2.5.1

• tensorflow-gpuPyPI

  From 2.3.0 · fixed in 2.3.4; From 2.4.0 · fixed in 2.4.3

• tensorflow-cpuPyPI

  From 2.3.0 · fixed in 2.3.4; From 2.4.0 · fixed in 2.4.3

References 2