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GHSA-368v-7v32-52fx
No affected components available
Impact
When tf.raw_ops.ResizeNearestNeighborGrad is given a large size input, it overflows.
import tensorflow as tf
align_corners = True
half_pixel_centers = False
grads = tf.constant(1, shape=[1,8,16,3], dtype=tf.float16)
size = tf.constant([1879048192,1879048192], shape=[2], dtype=tf.int32)
tf.raw_ops.ResizeNearestNeighborGrad(grads=grads, size=size, align_corners=align_corners, half_pixel_centers=half_pixel_centers)
Patches
We have patched the issue in GitHub commit 00c821af032ba9e5f5fa3fe14690c8d28a657624.
The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, 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 Neophytos Christou from the Secure Systems Lab (SSL) at Brown University.
The vulnerability can be exploited over the network without needing physical access. It is difficult for an attacker to exploit this vulnerability and may require special conditions. An attacker needs basic access or low-level privileges. The attacker needs the user to perform some action, like clicking a link. The impact is confined to the system where the vulnerability exists. There is a high impact on the availability of the system.
Exploitation attempts have been detected. Elevated vigilance and prompt remediation are advised.
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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