PyPi: Tensorflow

CVE-2021-37647

Safety vulnerability ID: 41122

This vulnerability was reviewed by experts

The information on this page was manually curated by our Cybersecurity Intelligence Team.

Created at Aug 12, 2021 Updated at Oct 25, 2024
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Advisory

TensorFlow 2.3.4, 2.4.3, 2.5.1 and 2.6.0 include a fix for CVE-2021-37647: When a user does not supply arguments that determine a valid sparse tensor, 'tf.raw_ops.SparseTensorSliceDataset' implementation can be made to dereference a null pointer. The implementation (https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L240-L251) has some argument validation but fails to consider the case when either 'indices' or 'values' are provided for an empty sparse tensor when the other is not. If 'indices' is empty, then code that performs validation (https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L260-L261) (i.e., checking that the indices are monotonically increasing) results in a null pointer dereference. If 'indices' as provided by the user is empty, then 'indices' in the C++ code above is backed by an empty 'std::vector', hence calling 'indices->dim_size(0)' results in null pointer dereferencing (same as calling 'std::vector::at()' on an empty vector). The Tensorflow team has patched the issue in GitHub commit 02cc160e29d20631de3859c6653184e3f876b9d7.

Affected package

tensorflow

Latest version: 2.18.0

TensorFlow is an open source machine learning framework for everyone.

Affected versions

Fixed versions

Vulnerability changelog

TensorFlow is an end-to-end open source platform for machine learning. When a user does not supply arguments that determine a valid sparse tensor, `tf.raw_ops.SparseTensorSliceDataset` implementation can be made to dereference a null pointer. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L240-L251) has some argument validation but fails to consider the case when either `indices` or `values` are provided for an empty sparse tensor when the other is not. If `indices` is empty, then [code that performs validation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L260-L261) (i.e., checking that the indices are monotonically increasing) results in a null pointer dereference. If `indices` as provided by the user is empty, then `indices` in the C++ code above is backed by an empty `std::vector`, hence calling `indices->dim_size(0)` results in null pointer dereferencing (same as calling `std::vector::at()` on an empty vector). We have patched the issue in GitHub commit 02cc160e29d20631de3859c6653184e3f876b9d7. 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. See CVE-2021-37647.


CONFIRM:https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c5x2-p679-95wc: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c5x2-p679-95wc
MISC:https://github.com/tensorflow/tensorflow/commit/02cc160e29d20631de3859c6653184e3f876b9d7: https://github.com/tensorflow/tensorflow/commit/02cc160e29d20631de3859c6653184e3f876b9d7

Resources

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Severity Details

CVSS Base Score

MEDIUM 5.5

CVSS v3 Details

MEDIUM 5.5
Attack Vector (AV)
LOCAL
Attack Complexity (AC)
LOW
Privileges Required (PR)
LOW
User Interaction (UI)
NONE
Scope (S)
UNCHANGED
Confidentiality Impact (C)
NONE
Integrity Impact (I)
NONE
Availability Availability (A)
HIGH

CVSS v2 Details

LOW 2.1
Access Vector (AV)
LOCAL
Access Complexity (AC)
LOW
Authentication (Au)
NONE
Confidentiality Impact (C)
NONE
Integrity Impact (I)
NONE
Availability Impact (A)
PARTIAL