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OpenAdvisories
Medium · 5.5 CVE-2021-37653 BIT-tensorflow-2021-37653EUVD-2021-0379GHSA-qjj8-32p7-h289PYSEC-2021-275PYSEC-2021-566PYSEC-2021-764

Division by 0 in `ResourceGather` 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 an attacker can trigger a crash via a floating point exception in `tf.raw_ops.ResourceGather`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L725-L731) computes the value of a value, `batch_size`, and then divides by it without checking that this value is not 0. We have patched the issue in GitHub commit ac117ee8a8ea57b73d34665cdf00ef3303bc0b11. 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-qjj8-32p7-h289
PyPI tensorflow >= 2.4.0, < 2.4.3 2.4.3 GHSA-qjj8-32p7-h289
PyPI tensorflow >= 2.5.0, < 2.5.1 2.5.1 GHSA-qjj8-32p7-h289
PyPI tensorflow >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-275
PyPI tensorflow-cpu < 2.3.4 2.3.4 GHSA-qjj8-32p7-h289
PyPI tensorflow-cpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-qjj8-32p7-h289
PyPI tensorflow-cpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-qjj8-32p7-h289
PyPI tensorflow-cpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-566
PyPI tensorflow-gpu < 2.3.4 2.3.4 GHSA-qjj8-32p7-h289
PyPI tensorflow-gpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-qjj8-32p7-h289
PyPI tensorflow-gpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-qjj8-32p7-h289
PyPI tensorflow-gpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-764

Advisories 1

References