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OpenAdvisories
Medium · 5.5 CVE-2021-37644 BIT-tensorflow-2021-37644EUVD-2021-0370GHSA-27j5-4p9v-pp67PYSEC-2021-266PYSEC-2021-557PYSEC-2021-755

`std::abort` raised from `TensorListReserve` 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 providing a negative element to `num_elements` list argument of `tf.raw_ops.TensorListReserve` causes the runtime to abort the process due to reallocating a `std::vector` to have a negative number of elements. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/list_kernels.cc#L312) calls `std::vector.resize()` with the new size controlled by input given by the user, without checking that this input is valid. We have patched the issue in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2. 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-27j5-4p9v-pp67
PyPI tensorflow >= 2.4.0, < 2.4.3 2.4.3 GHSA-27j5-4p9v-pp67
PyPI tensorflow >= 2.5.0, < 2.5.1 2.5.1 GHSA-27j5-4p9v-pp67
PyPI tensorflow >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-266
PyPI tensorflow-cpu < 2.3.4 2.3.4 GHSA-27j5-4p9v-pp67
PyPI tensorflow-cpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-27j5-4p9v-pp67
PyPI tensorflow-cpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-27j5-4p9v-pp67
PyPI tensorflow-cpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-557
PyPI tensorflow-gpu < 2.3.4 2.3.4 GHSA-27j5-4p9v-pp67
PyPI tensorflow-gpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-27j5-4p9v-pp67
PyPI tensorflow-gpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-27j5-4p9v-pp67
PyPI tensorflow-gpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-755

Advisories 1

References