TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.StringNGrams` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/string_ngrams_op.cc#L184) calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit c283e542a3f422420cfdb332414543b62fc4e4a5. 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.
History

No history.

cve-icon MITRE

Status: PUBLISHED

Assigner: GitHub_M

Published: 2021-08-12T21:10:11

Updated: 2024-08-04T01:23:01.254Z

Reserved: 2021-07-29T00:00:00

Link: CVE-2021-37646

cve-icon Vulnrichment

No data.

cve-icon NVD

Status : Analyzed

Published: 2021-08-12T21:15:07.983

Modified: 2021-08-18T15:39:10.807

Link: CVE-2021-37646

cve-icon Redhat

No data.