CVE-2022-29208

Description

### Impact The implementation of [`tf.raw_ops.EditDistance`]() has incomplete validation. Users can pass negative values to cause a segmentation fault based denial of service: ```python import tensorflow as tf hypothesis_indices = tf.constant(-1250999896764, shape=[3, 3], dtype=tf.int64) hypothesis_values = tf.constant(0, shape=[3], dtype=tf.int64) hypothesis_shape = tf.constant(0, shape=[3], dtype=tf.int64) truth_indices = tf.constant(-1250999896764, shape=[3, 3], dtype=tf.int64) truth_values = tf.constant(2, shape=[3], dtype=tf.int64) truth_shape = tf.constant(2, shape=[3], dtype=tf.int64) tf.raw_ops.EditDistance( hypothesis_indices=hypothesis_indices, hypothesis_values=hypothesis_values, hypothesis_shape=hypothesis_shape, truth_indices=truth_indices, truth_values=truth_values, truth_shape=truth_shape) ``` In multiple places throughout the code, we are computing an index for a write operation: ```cc if (g_truth == g_hypothesis) { auto loc = std::inner_product(g_truth.begin(), g_truth.end(), output_strides.begin(), int64_t{0}); OP_REQUIRES( ctx, loc < output_elements, errors::Internal("Got an inner product ", loc, " which would require in writing to outside of " "the buffer for the output tensor (max elements ", output_elements, ")")); output_t(loc) = gtl::LevenshteinDistance<T>(truth_seq, hypothesis_seq, cmp); // ... } ``` However, the existing validation only checks against the upper bound of the array. Hence, it is possible to write before the array by massaging the input to generate negative values for `loc`. ### Patches We have patched the issue in GitHub commit [30721cf564cb029d34535446d6a5a6357bebc8e7](https://github.com/tensorflow/tensorflow/commit/30721cf564cb029d34535446d6a5a6357bebc8e7). The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.

How to fix CVE-2022-29208

To remediate CVE-2022-29208, upgrade the affected package to a fixed version below.

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