Skip to content
OpenAdvisories
Low · 2.5 CVE-2021-29516 BIT-tensorflow-2021-29516EUVD-2021-0257GHSA-84mw-34w6-2q43PYSEC-2021-153PYSEC-2021-444PYSEC-2021-642

Null pointer dereference via invalid Ragged Tensors

Published May 14, 2021 · Updated Aug 3, 2024 · Assigned by GitHub_M

Description

TensorFlow is an end-to-end open source platform for machine learning. Calling `tf.raw_ops.RaggedTensorToVariant` with arguments specifying an invalid ragged tensor results in a null pointer dereference. The implementation of `RaggedTensorToVariant` operations(https://github.com/tensorflow/tensorflow/blob/904b3926ed1c6c70380d5313d282d248a776baa1/tensorflow/core/kernels/ragged_tensor_to_variant_op.cc#L39-L40) does not validate that the ragged tensor argument is non-empty. Since `batched_ragged` contains no elements, `batched_ragged.splits` is a null vector, thus `batched_ragged.splits(0)` will result in dereferencing `nullptr`. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Affected products

VendorProductAffectedFixed
tensorflow tensorflow < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 —

Affected packages

EcosystemPackageAffectedFixedRecord
PyPI tensorflow < 2.1.4 2.1.4 GHSA-84mw-34w6-2q43
PyPI tensorflow >= 2.2.0, < 2.2.3 2.2.3 GHSA-84mw-34w6-2q43
PyPI tensorflow >= 2.3.0, < 2.3.3 2.3.3 GHSA-84mw-34w6-2q43
PyPI tensorflow >= 2.4.0, < 2.4.2 2.4.2 GHSA-84mw-34w6-2q43
PyPI tensorflow < 2.1.4 · >= 2.2.0, < 2.2.3 · >= 2.3.0, < 2.3.3 · >= 2.4.0, < 2.4.2 2.1.4, 2.2.3, 2.3.3, 2.4.2 PYSEC-2021-153
PyPI tensorflow-cpu < 2.1.4 2.1.4 GHSA-84mw-34w6-2q43
PyPI tensorflow-cpu >= 2.2.0, < 2.2.3 2.2.3 GHSA-84mw-34w6-2q43
PyPI tensorflow-cpu >= 2.3.0, < 2.3.3 2.3.3 GHSA-84mw-34w6-2q43
PyPI tensorflow-cpu >= 2.4.0, < 2.4.2 2.4.2 GHSA-84mw-34w6-2q43
PyPI tensorflow-cpu < 2.1.4 · >= 2.2.0, < 2.2.3 · >= 2.3.0, < 2.3.3 · >= 2.4.0, < 2.4.2 2.1.4, 2.2.3, 2.3.3, 2.4.2 PYSEC-2021-444
PyPI tensorflow-gpu < 2.1.4 2.1.4 GHSA-84mw-34w6-2q43
PyPI tensorflow-gpu >= 2.2.0, < 2.2.3 2.2.3 GHSA-84mw-34w6-2q43
PyPI tensorflow-gpu >= 2.3.0, < 2.3.3 2.3.3 GHSA-84mw-34w6-2q43
PyPI tensorflow-gpu >= 2.4.0, < 2.4.2 2.4.2 GHSA-84mw-34w6-2q43
PyPI tensorflow-gpu < 2.1.4 · >= 2.2.0, < 2.2.3 · >= 2.3.0, < 2.3.3 · >= 2.4.0, < 2.4.2 2.1.4, 2.2.3, 2.3.3, 2.4.2 PYSEC-2021-642

References