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OpenAdvisories
Medium · 5.5 CVE-2021-37683 BIT-tensorflow-2021-37683EUVD-2021-0409GHSA-rhrq-64mq-hf9hPYSEC-2021-305PYSEC-2021-596PYSEC-2021-794

Division by zero in TensorFlow Lite division operations

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 division in TFLite is [vulnerable to a division by 0 error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/div.cc). There is no check that the divisor tensor does not contain zero elements. We have patched the issue in GitHub commit 1e206baedf8bef0334cca3eb92bab134ef525a28. 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-rhrq-64mq-hf9h
PyPI tensorflow >= 2.4.0, < 2.4.3 2.4.3 GHSA-rhrq-64mq-hf9h
PyPI tensorflow >= 2.5.0, < 2.5.1 2.5.1 GHSA-rhrq-64mq-hf9h
PyPI tensorflow >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-305
PyPI tensorflow-cpu < 2.3.4 2.3.4 GHSA-rhrq-64mq-hf9h
PyPI tensorflow-cpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-rhrq-64mq-hf9h
PyPI tensorflow-cpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-rhrq-64mq-hf9h
PyPI tensorflow-cpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-596
PyPI tensorflow-gpu < 2.3.4 2.3.4 GHSA-rhrq-64mq-hf9h
PyPI tensorflow-gpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-rhrq-64mq-hf9h
PyPI tensorflow-gpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-rhrq-64mq-hf9h
PyPI tensorflow-gpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-794

Advisories 1

References