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OpenAdvisories
Medium · 5.5 CVE-2021-37674 BIT-tensorflow-2021-37674EUVD-2021-0400GHSA-7ghq-fvr3-pj2xPYSEC-2021-296PYSEC-2021-587PYSEC-2021-785

Incomplete validation in `MaxPoolGrad` 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 denial of service via a segmentation fault in `tf.raw_ops.MaxPoolGrad` caused by missing validation. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/maxpooling_op.cc) misses some validation for the `orig_input` and `orig_output` tensors. The fixes for CVE-2021-29579 were incomplete. We have patched the issue in GitHub commit 136b51f10903e044308cf77117c0ed9871350475. 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-7ghq-fvr3-pj2x
PyPI tensorflow >= 2.4.0, < 2.4.3 2.4.3 GHSA-7ghq-fvr3-pj2x
PyPI tensorflow >= 2.5.0, < 2.5.1 2.5.1 GHSA-7ghq-fvr3-pj2x
PyPI tensorflow >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-296
PyPI tensorflow-cpu < 2.3.4 2.3.4 GHSA-7ghq-fvr3-pj2x
PyPI tensorflow-cpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-7ghq-fvr3-pj2x
PyPI tensorflow-cpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-7ghq-fvr3-pj2x
PyPI tensorflow-cpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-587
PyPI tensorflow-gpu < 2.3.4 2.3.4 GHSA-7ghq-fvr3-pj2x
PyPI tensorflow-gpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-7ghq-fvr3-pj2x
PyPI tensorflow-gpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-7ghq-fvr3-pj2x
PyPI tensorflow-gpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-785

Advisories 1

References