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Advisory Package Curation

CVE-2021-29528

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Advisory Summaries

github_osv/GHSA-6f84-42vf-ppwp

Division by 0 in `QuantizedMul` ### Impact An attacker can trigger a division by 0 in `tf.raw_ops.QuantizedMul`: ```python import tensorflow as tf x = tf.zeros([4, 1], dtype=tf.quint8) y = tf.constant([], dtype=tf.quint8) min_x = tf.constant(0.0) max_x = tf.constant(0.0010000000474974513) min_y = tf.constant(0.0) max_y = tf.constant(0.0010000000474974513) tf.raw_ops.QuantizedMul(x=x, y=y, min_x=min_x, max_x=max_x, min_y=min_y, max_y=max_y) ``` This is because the implementation https://github.com/tensorflow/tensorflow/blob/55900e961ed4a23b438392024912154a2c2f5e85/tensorflow/core/kernels/quantized_mul_op.cc#L188-L198 does a division by a quantity that is controlled by the caller: ```cc template <class T, class Toutput> void VectorTensorMultiply(const T* vector_data, int32 vector_offset, int64 vector_num_elements, const T* tensor_data, int32 tensor_offset, int64 tensor_num_elements, Toutput* output) { for (int i = 0; i < tensor_num_elements; ++i) { const int64 vector_i = i % vector_num_elements; ... } } ``` ### Patches We have patched the issue in GitHub commit a1b11d2fdd1e51bfe18bb1ede804f60abfa92da6 https://github.com/tensorflow/tensorflow/commit/a1b11d2fdd1e51bfe18bb1ede804f60abfa92da6. 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.

gitlab/pypi/tensorflow/CVE-2021-29528

Division by 0 in `QuantizedMul` An attacker can trigger a division by 0 in `tf.raw_ops.QuantizedMul`: ```python import tensorflow as tf x = tf.zeros([4, 1], dtype=tf.quint8) y = tf.constant([], dtype=tf.quint8) min_x = tf.constant(0.0) max_x = tf.constant(0.0010000000474974513) min_y = tf.constant(0.0) max_y = tf.constant(0.0010000000474974513) tf.raw_ops.QuantizedMul(x=x, y=y, min_x=min_x, max_x=max_x, min_y=min_y, max_y=max_y) ```

pypa/tensorflow/PYSEC-2021-165

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.QuantizedMul`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55900e961ed4a23b438392024912154a2c2f5e85/tensorflow/core/kernels/quantized_mul_op.cc#L188-L198) does a division by a quantity that is controlled by the caller. 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.

pysec/PYSEC-2021-165

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.QuantizedMul`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55900e961ed4a23b438392024912154a2c2f5e85/tensorflow/core/kernels/quantized_mul_op.cc#L188-L198) does a division by a quantity that is controlled by the caller. 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.