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OpenAdvisories
Medium · 5.5 CVE-2021-37642 BIT-tensorflow-2021-37642EUVD-2021-0368GHSA-ch4f-829c-v5pwPYSEC-2021-264PYSEC-2021-555PYSEC-2021-753

Division by 0 in `ResourceScatterDiv` in TensorFlow

Published Aug 12, 2021 · Updated Aug 4, 2024 · Assigned by GitHub_M

Description

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.ResourceScatterDiv` is vulnerable to a division by 0 error. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/resource_variable_ops.cc#L865) uses a common class for all binary operations but fails to treat the division by 0 case separately. We have patched the issue in GitHub commit 4aacb30888638da75023e6601149415b39763d76. 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.

Affected products

VendorProductAffectedFixed
tensorflow tensorflow >= 2.5.0, < 2.5.1, >= 2.4.0, < 2.4.3, < 2.3.4 —

Fixed in Linux distributions

Distributions backport fixes, so the version that fixes this vulnerability differs per release — upgrade to at least the version shown. From the distributions' security trackers and advisories.

ReleasePackageFixed inAdvisory
SUSE Package Hub 15 SP3 bazel-skylib1.0.3 1.0.3-bp153.2.1 openSUSE-SU-2022:10014-1
SUSE Package Hub 15 SP3 bazel3.7 3.7.2-bp153.4.1 openSUSE-SU-2022:10014-1
SUSE Package Hub 15 SP3 tensorflow2 +3 2.6.0-bp153.2.3.1 openSUSE-SU-2022:10014-1
ReleasePackageFixed inAdvisory
openSUSE Leap 15.3 bazel-skylib1.0.3 1.0.3-bp153.2.1 openSUSE-SU-2022:10014-1
openSUSE Leap 15.3 bazel3.7 3.7.2-bp153.4.1 openSUSE-SU-2022:10014-1
openSUSE Leap 15.3 tensorflow2 +3 2.6.0-bp153.2.3.1 openSUSE-SU-2022:10014-1

Affected packages

EcosystemPackageAffectedFixedRecord
PyPI tensorflow < 2.3.4 2.3.4 GHSA-ch4f-829c-v5pw
PyPI tensorflow >= 2.4.0, < 2.4.3 2.4.3 GHSA-ch4f-829c-v5pw
PyPI tensorflow >= 2.5.0, < 2.5.1 2.5.1 GHSA-ch4f-829c-v5pw
PyPI tensorflow >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-264
PyPI tensorflow-cpu < 2.3.4 2.3.4 GHSA-ch4f-829c-v5pw
PyPI tensorflow-cpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-ch4f-829c-v5pw
PyPI tensorflow-cpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-ch4f-829c-v5pw
PyPI tensorflow-cpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-555
PyPI tensorflow-gpu < 2.3.4 2.3.4 GHSA-ch4f-829c-v5pw
PyPI tensorflow-gpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-ch4f-829c-v5pw
PyPI tensorflow-gpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-ch4f-829c-v5pw
PyPI tensorflow-gpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-753

Advisories 1

References