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GHSA-pfjj-m3jj-9jc9
No affected components available
Impact
The implementation of SparseTensorSliceDataset has an undefined behavior: under certain condition it can be made to dereference a nullptr value:
import tensorflow as tf
import numpy as np
tf.raw_ops.SparseTensorSliceDataset(
indices=[[]],
values=[],
dense_shape=[1,1])
The 3 input arguments represent a sparse tensor. However, there are some preconditions that these arguments must satisfy but these are not validated in the implementation.
Patches
We have patched the issue in GitHub commit 965b97e4a9650495cda5a8c210ef6684b4b9eceb.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Faysal Hossain Shezan from University of Virginia.
The vulnerability can be exploited over the network without needing physical access. 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 low impact on the confidentiality of the information. There is a low 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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