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.
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cve-icon MITRE

Status: PUBLISHED

Assigner: GitHub_M

Published: 2021-05-14T19:35:49

Updated: 2024-08-03T22:11:05.725Z

Reserved: 2021-03-30T00:00:00

Link: CVE-2021-29521

cve-icon Vulnrichment

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cve-icon NVD

Status : Analyzed

Published: 2021-05-14T20:15:11.567

Modified: 2021-05-20T17:19:30.450

Link: CVE-2021-29521

cve-icon Redhat

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