TensorFlow is an end-to-end open source platform for machine learning. If the `splits` argument of `RaggedBincount` does not specify a valid `SparseTensor`(https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor), then an attacker can trigger a heap buffer overflow. This will cause a read from outside the bounds of the `splits` tensor buffer in the implementation of the `RaggedBincount` op(https://github.com/tensorflow/tensorflow/blob/8b677d79167799f71c42fd3fa074476e0295413a/tensorflow/core/kernels/bincount_op.cc#L430-L433). Before the `for` loop, `batch_idx` is set to 0. The user controls the `splits` array, making it contain only one element, 0. Thus, the code in the `while` loop would increment `batch_idx` and then try to read `splits(1)`, which is outside of bounds. 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, as these are also affected.
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cve-icon MITRE

Status: PUBLISHED

Assigner: GitHub_M

Published: 2021-05-14T18:55:10

Updated: 2024-08-03T22:11:05.767Z

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

Link: CVE-2021-29512

cve-icon Vulnrichment

No data.

cve-icon NVD

Status : Modified

Published: 2021-05-14T19:15:07.753

Modified: 2024-11-21T06:01:16.970

Link: CVE-2021-29512

cve-icon Redhat

No data.