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OpenAdvisories
Medium · 4.4 CVE-2021-37682 BIT-tensorflow-2021-37682EUVD-2021-0408GHSA-4c4g-crqm-xrxwPYSEC-2021-304PYSEC-2021-595PYSEC-2021-793

Use of unitialized value in TensorFlow Lite

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 all TFLite operations that use quantization can be made to use unitialized values. [For example](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/depthwise_conv.cc#L198-L200). The issue stems from the fact that `quantization.params` is only valid if `quantization.type` is different that `kTfLiteNoQuantization`. However, these checks are missing in large parts of the code. We have patched the issue in GitHub commits 537bc7c723439b9194a358f64d871dd326c18887, 4a91f2069f7145aab6ba2d8cfe41be8a110c18a5 and 8933b8a21280696ab119b63263babdb54c298538. 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-4c4g-crqm-xrxw
PyPI tensorflow >= 2.4.0, < 2.4.3 2.4.3 GHSA-4c4g-crqm-xrxw
PyPI tensorflow >= 2.5.0, < 2.5.1 2.5.1 GHSA-4c4g-crqm-xrxw
PyPI tensorflow >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-304
PyPI tensorflow-cpu < 2.3.4 2.3.4 GHSA-4c4g-crqm-xrxw
PyPI tensorflow-cpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-4c4g-crqm-xrxw
PyPI tensorflow-cpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-4c4g-crqm-xrxw
PyPI tensorflow-cpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-595
PyPI tensorflow-gpu < 2.3.4 2.3.4 GHSA-4c4g-crqm-xrxw
PyPI tensorflow-gpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-4c4g-crqm-xrxw
PyPI tensorflow-gpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-4c4g-crqm-xrxw
PyPI tensorflow-gpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-793

Advisories 1

References