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OpenAdvisories
High · 7.8 CVE-2021-37671 BIT-tensorflow-2021-37671EUVD-2021-0397GHSA-qr82-2c78-4m8hPYSEC-2021-293PYSEC-2021-584PYSEC-2021-782

Reference binding to nullptr in map operations 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 cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.Map*` and `tf.raw_ops.OrderedMap*` operations. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L222-L248) has a check in place to ensure that `indices` is in ascending order, but does not check that `indices` is not empty. We have patched the issue in GitHub commit 532f5c5a547126c634fefd43bbad1dc6417678ac. 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-qr82-2c78-4m8h
PyPI tensorflow >= 2.4.0, < 2.4.3 2.4.3 GHSA-qr82-2c78-4m8h
PyPI tensorflow >= 2.5.0, < 2.5.1 2.5.1 GHSA-qr82-2c78-4m8h
PyPI tensorflow >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-293
PyPI tensorflow-cpu < 2.3.4 2.3.4 GHSA-qr82-2c78-4m8h
PyPI tensorflow-cpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-qr82-2c78-4m8h
PyPI tensorflow-cpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-qr82-2c78-4m8h
PyPI tensorflow-cpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-584
PyPI tensorflow-gpu < 2.3.4 2.3.4 GHSA-qr82-2c78-4m8h
PyPI tensorflow-gpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-qr82-2c78-4m8h
PyPI tensorflow-gpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-qr82-2c78-4m8h
PyPI tensorflow-gpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-782

Advisories 1

References