In TensorFlow before version 2.6.0 an attacker can trigger a crash via a CHECK-fail in debug builds of TensorFlow using tf.raw_ops.ResourceGather or a read from outside the bounds of heap allocated data in the same API in a release build. The implementation does not check that the batch_dims value that the user supplies is less than the rank of the input tensor. Since the implementation uses several for loops over the dimensions of tensor, this results in reading data from outside the bounds of heap allocated buffer backing the tensor.
In TensorFlow before version 2.6.0 an attacker can trigger a crash via a CHECK-fail in debug builds of TensorFlow using tf.raw_ops.ResourceGather or a read from outside the bounds of heap allocated data in the same API in a release build. The implementation does not check that the batch_dims value that the user supplies is less than the rank of the input tensor. Since the implementation uses several for loops over the dimensions of tensor, this results in reading data from outside the bounds of heap allocated buffer backing the tensor.
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2r8p-fg3c-wcj4 https://github.com/tensorflow/tensorflow/commit/bc9c546ce7015c57c2f15c168b3d9201de679a1d
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