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GHSA-vwhq-49r4-gj9v
No affected components available
Impact
The shape inference code for tf.ragged.cross has an undefined behavior due to binding a reference to nullptr. In the following scenario, this results in a crash:
import tensorflow as tf
@tf.function
def test():
y = tf.ragged.cross([tf.ragged.constant([['1']]),'2'])
return y
test()
Patches
We have patched the issue in GitHub commit fa6b7782fbb14aa08d767bc799c531f5e1fb3bb8.
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
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 members of the Aivul Team from Qihoo 360.
The vulnerability requires local access to the device to be exploited. It is easy for an attacker to exploit this vulnerability. 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 high impact on the confidentiality of the information. There is a high impact on the integrity of the data. There is a high impact on the availability of the system.
Exploitation activity has been observed. Apply available patches or mitigations urgently.
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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