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Severe, 6 weeks1498Projects326

1498 severe, 6 weeks · 326 projects

TensorFlowGHSA-c5x2-p679-95wc

Null pointer dereference in `SparseTensorSliceDataset`

TensorFlow

CVE-2021-37647 · Published Aug 25, 2021 · updated Jul 8, 2026

High7.7
Fix: upgrade to 2.3.4 or later (3 fixed versions below)
GitHub advisory

Impact

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:

```python

import tensorflow as tf

tf.raw_ops.SparseTensorSliceDataset(

indices=[[],[],[]],

values=[1,2,3],

dense_shape=[3,3])

`

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 (as in the example above), 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:

```cc

for (int64_t i = 0; i < indices->dim_size(0); ++i) {

int64_t next_batch_index = indices->matrix<int64>()(i, 0);

...

}

`

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...

Affected versions

PackageAffectedFixed in
tensorflow
PyPI
< 2.3.42.3.4
>= 2.4.0, < 2.4.32.4.3
>= 2.5.0, < 2.5.12.5.1
Details and references

### Impact 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: ```python import tensorflow as tf tf.raw_ops.SparseTensorSliceDataset( indices=[[],[],[]], values=[1,2,3], dense_shape=[3,3]) ``` 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 (as in the example above), 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: ```cc for (int64_t i = 0; i < indices->dim_size(0); ++i) { int64_t next_batch_index = indices->matrix<int64>()(i, 0); ... } ``` 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). ### Patches We have patched the issue in GitHub commit [02cc160e29d20631de3859c6653184e3f876b9d7](https://github.com/tensorflow/tensorflow/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. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by members of the Aivul Team from Qihoo 360.

CVSS 3.1
CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:H
Severity from
GitHub (reviewed advisory)
Weakness
CWE-476
Also known as
BIT-tensorflow-2021-37647, CVE-2021-37647, PYSEC-2021-269, PYSEC-2021-560, PYSEC-2021-758

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