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OpenAdvisories
Medium · 5.5 CVE-2021-37670 BIT-tensorflow-2021-37670EUVD-2021-0396GHSA-9697-98pf-4rw7PYSEC-2021-292PYSEC-2021-583PYSEC-2021-781

Heap OOB in `UpperBound` and `LowerBound` 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 read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.UpperBound`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/searchsorted_op.cc#L85-L104) does not validate the rank of `sorted_input` argument. A similar issue occurs in `tf.raw_ops.LowerBound`. We have patched the issue in GitHub commit 42459e4273c2e47a3232cc16c4f4fff3b3a35c38. 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-9697-98pf-4rw7
PyPI tensorflow >= 2.4.0, < 2.4.3 2.4.3 GHSA-9697-98pf-4rw7
PyPI tensorflow >= 2.5.0, < 2.5.1 2.5.1 GHSA-9697-98pf-4rw7
PyPI tensorflow >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-292
PyPI tensorflow-cpu < 2.3.4 2.3.4 GHSA-9697-98pf-4rw7
PyPI tensorflow-cpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-9697-98pf-4rw7
PyPI tensorflow-cpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-9697-98pf-4rw7
PyPI tensorflow-cpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-583
PyPI tensorflow-gpu < 2.3.4 2.3.4 GHSA-9697-98pf-4rw7
PyPI tensorflow-gpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-9697-98pf-4rw7
PyPI tensorflow-gpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-9697-98pf-4rw7
PyPI tensorflow-gpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-781

Advisories 1

References