| Package | Affected versions | Patched versions |
|---|---|---|
| tensorflow | ≥ 2.5.0, < 2.5.2≥ 2.6.0, < 2.6.1≥ 2.7.0rc0, < 2.7.0< 2.4.4 | 2.5.22.6.12.7.02.4.4 |
| tensorflow-cpu | ≥ 2.5.0, < 2.5.2≥ 2.6.0, < 2.6.1≥ 2.7.0rc0, < 2.7.0< 2.4.4 | 2.5.22.6.12.7.02.4.4 |
| tensorflow-gpu | ≥ 2.5.0, < 2.5.2≥ 2.6.0, < 2.6.1≥ 2.7.0rc0, < 2.7.0< 2.4.4 | 2.5.22.6.12.7.02.4.4 |
| tensorflow | = 2.6.0≥ 2.5.0, < 2.5.2< 2.4.4 | 2.5.22.4.4 |
The shape inference functions for SparseCountSparseOutput can trigger a read outside of bounds of heap allocated array:
import tensorflow as tf
@tf.function
def func():
return tf.raw_ops.SparseCountSparseOutput(
indices=[1],
values=[[1]],
dense_shape=[10],
weights=[],
binary_output= True)
func()
The function fails to check that the first input (i.e., indices) has rank 2:
auto rank = c->Dim(c->input(0), 1);
We have patched the issue in GitHub commit 701cfaca222a82afbeeb17496bd718baa65a67d2.
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.
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 members of the Aivul Team from Qihoo 360.
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