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GHSA-9rpc-5v9q-5r7f
No affected components available
Impact
Incomplete validation in SparseReshape results in a denial of service based on a CHECK-failure.
import tensorflow as tf
input_indices = tf.constant(41, shape=[1, 1], dtype=tf.int64)
input_shape = tf.zeros([11], dtype=tf.int64)
new_shape = tf.zeros([1], dtype=tf.int64)
tf.raw_ops.SparseReshape(input_indices=input_indices,
input_shape=input_shape,
new_shape=new_shape)
The implementation has no validation that the input arguments specify a valid sparse tensor.
Patches
We have patched the issue in GitHub commit 1d04d7d93f4ed3854abf75d6b712d72c3f70d6b6.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3, as these are the only affected versions.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team.
The vulnerability requires local access to the device to be exploited. It is difficult for an attacker to exploit this vulnerability and may require special conditions. An attacker needs basic access or low-level privileges. No user interaction is needed for the attacker to exploit this vulnerability. The impact is confined to the system where the vulnerability exists. There is a low impact on the integrity of the data. There is a low impact on the availability of the system.
Limited exploitation activity has been observed. Close monitoring and planned remediation are recommended.
The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.
We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.
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