| Package | Affected versions | Patched versions |
|---|---|---|
| tensorflow | ≥ 2.3.0, < 2.3.4≥ 2.4.0, < 2.4.3≥ 2.5.0, < 2.5.1< 2.3.4 | 2.3.42.4.32.5.1 |
| tensorflow-cpu | ≥ 2.3.0, < 2.3.4≥ 2.4.0, < 2.4.3≥ 2.5.0, < 2.5.1< 2.3.4 | 2.3.42.4.32.5.1 |
| tensorflow-gpu | ≥ 2.3.0, < 2.3.4≥ 2.4.0, < 2.4.3≥ 2.5.0, < 2.5.1< 2.3.4 | 2.3.42.4.32.5.1 |
| tensorflow | = 2.5.0= 2.6.0≥ 2.3.0, < 2.3.4≥ 2.4.0, < 2.4.3 | 2.3.42.4.3 |
An attacker can cause undefined behavior via binding a reference to null pointer in tf.raw_ops.SparseFillEmptyRows:
import tensorflow as tf
tf.compat.v1.disable_v2_behavior()
tf.raw_ops.SparseFillEmptyRows(
indices = tf.constant([], shape=[0, 0], dtype=tf.int64),
values = tf.constant([], shape=[0], dtype=tf.int64),
dense_shape = tf.constant([], shape=[0], dtype=tf.int64),
default_value = 0)
The shape inference implementation does not validate that the input arguments are not empty tensors.
We have patched the issue in GitHub commit 578e634b4f1c1c684d4b4294f9e5281b2133b3ed.
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 Yakun Zhang of Baidu Security
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