CVE-2021-29578
LOW2.5EPSS 0.01%Heap buffer overflow in `FractionalAvgPoolGrad`
描述
### 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](https://github.com/tensorflow/tensorflow/blob/dcba796a28364d6d7f003f6fe733d82726dda713/tensorflow/core/kernels/fractional_avg_pool_op.cc#L216) 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](https://github.com/tensorflow/tensorflow/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](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.
受影響套件(7)
- Bitnami/tensorflowfrom 0, < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2
- PyPI/tensorflowfrom 0, < 2.1.4
- PyPI/tensorflowfrom 0, < 12c727cee857fa19be717f336943d95fca4ffe4f | from 0, < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2
- PyPI/tensorflow-cpufrom 0, < 12c727cee857fa19be717f336943d95fca4ffe4f | from 0, < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2
- PyPI/tensorflow-cpufrom 0, < 2.1.4
- PyPI/tensorflow-gpufrom 0, < 12c727cee857fa19be717f336943d95fca4ffe4f | from 0, < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2
- PyPI/tensorflow-gpufrom 0, < 2.1.4
CVSS 分數
| 來源 | 版本 | 嚴重程度 | 向量 |
|---|---|---|---|
| osv | CVSS 4.0 | — | CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N |
| osv | CVSS 3.1 | LOW2.5 | CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L |
參考連結(7)
- ADVISORYhttps://nvd.nist.gov/vuln/detail/CVE-2021-29578
- PATCHhttps://github.com/tensorflow/tensorflow
- WEBhttps://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-506.yaml
- WEBhttps://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-704.yaml
- WEBhttps://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-215.yaml
- WEBhttps://github.com/tensorflow/tensorflow/commit/12c727cee857fa19be717f336943d95fca4ffe4f
- WEBhttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-6f89-8j54-29xf