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Advisory Package Curation

CVE-2021-29565

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Advisory Summaries

github_osv/GHSA-r6pg-pjwc-j585

Null pointer dereference in `SparseFillEmptyRows` ### Impact An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.SparseFillEmptyRows`: ```python import tensorflow as tf indices = tf.constant([], shape=[0, 0], dtype=tf.int64) values = tf.constant([], shape=[0], dtype=tf.int64) dense_shape = tf.constant([], shape=[0], dtype=tf.int64) default_value = 0 tf.raw_ops.SparseFillEmptyRows( indices=indices, values=values, dense_shape=dense_shape, default_value=default_value) ``` This is because of missing validation https://github.com/tensorflow/tensorflow/blob/fdc82089d206e281c628a93771336bf87863d5e8/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L230-L231 that was covered under a `TODO`. If the `dense_shape` tensor is empty, then `dense_shape_t.vec<>()` would cause a null pointer dereference in the implementation of the op: ```cc template <typename T, typename Tindex> struct SparseFillEmptyRows<CPUDevice, T, Tindex> { Status operator()(OpKernelContext* context, const Tensor& default_value_t, const Tensor& indices_t, const Tensor& values_t, const Tensor& dense_shape_t, typename AsyncOpKernel::DoneCallback done) { ... const auto dense_shape = dense_shape_t.vec<Tindex>(); ... } } ``` ### Patches We have patched the issue in GitHub commit faa76f39014ed3b5e2c158593b1335522e573c7f https://github.com/tensorflow/tensorflow/commit/faa76f39014ed3b5e2c158593b1335522e573c7f. 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 Yakun Zhang and Ying Wang of Baidu X-Team.

gitlab/pypi/tensorflow/CVE-2021-29565

Null pointer dereference in `SparseFillEmptyRows` An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.SparseFillEmptyRows`: ```python import tensorflow as tf indices = tf.constant([], shape=[0, 0], dtype=tf.int64) values = tf.constant([], shape=[0], dtype=tf.int64) dense_shape = tf.constant([], shape=[0], dtype=tf.int64) default_value = 0 tf.raw_ops.SparseFillEmptyRows( indices=indices, values=values, dense_shape=dense_shape, default_value=default_value) ```

pypa/tensorflow/PYSEC-2021-202

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.SparseFillEmptyRows`. This is because of missing validation(https://github.com/tensorflow/tensorflow/blob/fdc82089d206e281c628a93771336bf87863d5e8/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L230-L231) that was covered under a `TODO`. If the `dense_shape` tensor is empty, then `dense_shape_t.vec<>()` would cause a null pointer dereference in the implementation of the op. 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-2021-202

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.SparseFillEmptyRows`. This is because of missing validation(https://github.com/tensorflow/tensorflow/blob/fdc82089d206e281c628a93771336bf87863d5e8/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L230-L231) that was covered under a `TODO`. If the `dense_shape` tensor is empty, then `dense_shape_t.vec<>()` would cause a null pointer dereference in the implementation of the op. 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.