Skip to content
OpenAdvisories
High · 7.8 CVE-2021-37650 BIT-tensorflow-2021-37650EUVD-2021-0376GHSA-f8h4-7rgh-q2gmPYSEC-2021-272PYSEC-2021-563PYSEC-2021-761

Segfault and heap buffer overflow in `{Experimental,}DatasetToTFRecord` 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 the implementation for `tf.raw_ops.ExperimentalDatasetToTFRecord` and `tf.raw_ops.DatasetToTFRecord` can trigger heap buffer overflow and segmentation fault. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc#L93-L102) assumes that all records in the dataset are of string type. However, there is no check for that, and the example given above uses numeric types. We have patched the issue in GitHub commit e0b6e58c328059829c3eb968136f17aa72b6c876. 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-f8h4-7rgh-q2gm
PyPI tensorflow >= 2.4.0, < 2.4.3 2.4.3 GHSA-f8h4-7rgh-q2gm
PyPI tensorflow >= 2.5.0, < 2.5.1 2.5.1 GHSA-f8h4-7rgh-q2gm
PyPI tensorflow >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-272
PyPI tensorflow-cpu < 2.3.4 2.3.4 GHSA-f8h4-7rgh-q2gm
PyPI tensorflow-cpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-f8h4-7rgh-q2gm
PyPI tensorflow-cpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-f8h4-7rgh-q2gm
PyPI tensorflow-cpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-563
PyPI tensorflow-gpu < 2.3.4 2.3.4 GHSA-f8h4-7rgh-q2gm
PyPI tensorflow-gpu >= 2.4.0, < 2.4.3 2.4.3 GHSA-f8h4-7rgh-q2gm
PyPI tensorflow-gpu >= 2.5.0, < 2.5.1 2.5.1 GHSA-f8h4-7rgh-q2gm
PyPI tensorflow-gpu >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 2.3.4, 2.4.3 PYSEC-2021-761

Advisories 1

References