Advisoriesby IbisHeap OOB access in unicode ops
Impact
An attacker can access data outside of bounds of heap allocated array in tf.raw_ops.UnicodeEncode:
```python
import tensorflow as tf
input_values = tf.constant([58], shape=[1], dtype=tf.int32)
input_splits = tf.constant([[81, 101, 0]], shape=[3], dtype=tf.int32)
output_encoding = "UTF-8"
tf.raw_ops.UnicodeEncode(
input_values=input_values, input_splits=input_splits,
output_encoding=output_encoding)
`
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/472c1f12ad9063405737679d4f6bd43094e1d36d/tensorflow/core/kernels/unicode_ops.cc)
assumes that the input_value/input_splits pair specify a valid sparse tensor.
Patches
We have patched the issue in GitHub commit [51300ba1cc2f487aefec6e6631fef03b0e08b298](https://github.com/tensorflow/tensorflow/commit/51300ba1cc2f487aefec6e6631fef03b0e08b298).
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...
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 access data outside of bounds of heap allocated array in `tf.raw_ops.UnicodeEncode`: ```python import tensorflow as tf input_values = tf.constant([58], shape=[1], dtype=tf.int32) input_splits = tf.constant([[81, 101, 0]], shape=[3], dtype=tf.int32) output_encoding = "UTF-8" tf.raw_ops.UnicodeEncode( input_values=input_values, input_splits=input_splits, output_encoding=output_encoding) ``` This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/472c1f12ad9063405737679d4f6bd43094e1d36d/tensorflow/core/kernels/unicode_ops.cc) assumes that the `input_value`/`input_splits` pair specify a valid sparse tensor. ### Patches We have patched the issue in GitHub commit [51300ba1cc2f487aefec6e6631fef03b0e08b298](https://github.com/tensorflow/tensorflow/commit/51300ba1cc2f487aefec6e6631fef03b0e08b298). 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-125
- Also known as
- BIT-tensorflow-2021-29559, CVE-2021-29559, PYSEC-2021-196, PYSEC-2021-487, PYSEC-2021-685
- github.com/tensorflow/tensorflow/security/advisories/GHSA-59q2-x2qc-4c97
- nvd.nist.gov/vuln/detail/CVE-2021-29559
- github.com/tensorflow/tensorflow/commit/51300ba1cc2f487aefec6e6631fef03b0e08b298
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-487.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-685.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-196.yaml
- github.com/tensorflow/tensorflow
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