Null pointer exception in `DeserializeSparse`
Impact
The [shape inference code for DeserializeSparse](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/ops/sparse_ops.cc#L152-L168) can trigger a null pointer dereference:
```python
import tensorflow as tf
dataset = tf.data.Dataset.range(3)
@tf.function
def test():
y = tf.raw_ops.DeserializeSparse(
serialized_sparse=tf.data.experimental.to_variant(dataset),
dtype=tf.int32)
test()
`
This is because the shape inference function assumes that the serialize_sparse tensor is a tensor with positive rank (and having 3 as the last dimension). However, in the example above, the argument is a scalar (i.e., rank 0).
Patches
We have patched the issue in GitHub commit [d3738dd70f1c9ceb547258cbb82d853da8771850](https://github.com/tensorflow/tensorflow/commit/d3738dd70f1c9ceb547258cbb82d853da8771850).
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 members of the Aivul Team...
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | >= 2.6.0, < 2.6.1 | 2.6.1 |
| >= 2.5.0, < 2.5.2 | 2.5.2 | |
| < 2.4.4 | 2.4.4 |
Details and references
### Impact The [shape inference code for `DeserializeSparse`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/ops/sparse_ops.cc#L152-L168) can trigger a null pointer dereference: ```python import tensorflow as tf dataset = tf.data.Dataset.range(3) @tf.function def test(): y = tf.raw_ops.DeserializeSparse( serialized_sparse=tf.data.experimental.to_variant(dataset), dtype=tf.int32) test() ``` This is because the shape inference function assumes that the `serialize_sparse` tensor is a tensor with positive rank (and having `3` as the last dimension). However, in the example above, the argument is a scalar (i.e., rank 0). ### Patches We have patched the issue in GitHub commit [d3738dd70f1c9ceb547258cbb82d853da8771850](https://github.com/tensorflow/tensorflow/commit/d3738dd70f1c9ceb547258cbb82d853da8771850). The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 members of the Aivul Team from Qihoo 360.
- CVSS 3.1
- CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-476
- Also known as
- BIT-tensorflow-2021-41215, CVE-2021-41215, PYSEC-2021-407, PYSEC-2021-624, PYSEC-2021-822
- github.com/tensorflow/tensorflow/security/advisories/GHSA-x3v8-c8qx-3j3r
- nvd.nist.gov/vuln/detail/CVE-2021-41215
- github.com/tensorflow/tensorflow/commit/d3738dd70f1c9ceb547258cbb82d853da8771850
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-624.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-822.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-407.yaml
- github.com/tensorflow/tensorflow