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OpenAdvisories
High · 7.7 CVE-2021-37643 BIT-tensorflow-2021-37643EUVD-2021-0369GHSA-fcwc-p4fc-c5ccPYSEC-2021-265PYSEC-2021-556PYSEC-2021-754

Null pointer dereference in `MatrixDiagPartOp` 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. If a user does not provide a valid padding value to `tf.raw_ops.MatrixDiagPartOp`, then the code triggers a null pointer dereference (if input is empty) or produces invalid behavior, ignoring all values after the first. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/linalg/matrix_diag_op.cc#L89) reads the first value from a tensor buffer without first checking that the tensor has values to read from. We have patched the issue in GitHub commit 482da92095c4d48f8784b1f00dda4f81c28d2988. 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-fcwc-p4fc-c5cc
PyPI tensorflow >= 2.4.0, < 2.4.3 2.4.3 GHSA-fcwc-p4fc-c5cc
PyPI tensorflow >= 2.5.0, < 2.5.1 2.5.1 GHSA-fcwc-p4fc-c5cc
PyPI tensorflow >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-265
PyPI tensorflow-cpu < 2.3.4 2.3.4 GHSA-fcwc-p4fc-c5cc
PyPI tensorflow-cpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-fcwc-p4fc-c5cc
PyPI tensorflow-cpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-fcwc-p4fc-c5cc
PyPI tensorflow-cpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-556
PyPI tensorflow-gpu < 2.3.4 2.3.4 GHSA-fcwc-p4fc-c5cc
PyPI tensorflow-gpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-fcwc-p4fc-c5cc
PyPI tensorflow-gpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-fcwc-p4fc-c5cc
PyPI tensorflow-gpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-754

Advisories 1

References