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OpenAdvisories
High · 7.7 CVE-2021-37637 BIT-tensorflow-2021-37637EUVD-2021-0363GHSA-c9qf-r67m-p7cgPYSEC-2021-259PYSEC-2021-550PYSEC-2021-748

Null pointer dereference in `CompressElement` 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. It is possible to trigger a null pointer dereference in TensorFlow by passing an invalid input to `tf.raw_ops.CompressElement`. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/data/compression_utils.cc#L34) was accessing the size of a buffer obtained from the return of a separate function call before validating that said buffer is valid. We have patched the issue in GitHub commit 5dc7f6981fdaf74c8c5be41f393df705841fb7c5. 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-c9qf-r67m-p7cg
PyPI tensorflow >= 2.4.0, < 2.4.3 2.4.3 GHSA-c9qf-r67m-p7cg
PyPI tensorflow >= 2.5.0, < 2.5.1 2.5.1 GHSA-c9qf-r67m-p7cg
PyPI tensorflow >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-259
PyPI tensorflow-cpu < 2.3.4 2.3.4 GHSA-c9qf-r67m-p7cg
PyPI tensorflow-cpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-c9qf-r67m-p7cg
PyPI tensorflow-cpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-c9qf-r67m-p7cg
PyPI tensorflow-cpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-550
PyPI tensorflow-gpu < 2.3.4 2.3.4 GHSA-c9qf-r67m-p7cg
PyPI tensorflow-gpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-c9qf-r67m-p7cg
PyPI tensorflow-gpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-c9qf-r67m-p7cg
PyPI tensorflow-gpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-748

Advisories 1

References