| Package | Affected versions | Patched versions |
|---|---|---|
| tensorflow | ≥ 2.10.0, < 2.10.1≥ 2.9.0, < 2.9.3< 2.8.4 | 2.10.12.9.32.8.4 |
| tensorflow-cpu | ≥ 2.10.0, < 2.10.1≥ 2.9.0, < 2.9.3< 2.8.4 | 2.10.12.9.32.8.4 |
| tensorflow-gpu | ≥ 2.10.0, < 2.10.1≥ 2.9.0, < 2.9.3< 2.8.4 | 2.10.12.9.32.8.4 |
| tensorflow | = 2.10.0≥ 2.9.0, < 2.9.3< 2.8.4 | 2.9.32.8.4 |
If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. E.g. the following raises an error:
np.ones((0, 2**31, 2**31))
An example of a proof of concept:
import numpy as np
import tensorflow as tf
input_val = tf.constant([1])
shape_val = np.array([i for i in range(21)])
tf.broadcast_to(input=input_val,shape=shape_val)
The return value of PyArray_SimpleNewFromData, which returns null on such shapes, is not checked.
We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784.
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.
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
This vulnerability has been reported by Pattarakrit Rattanukul.
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