Lack of data validation In tensorflow-cpu
Description
TensorFlow vulnerable to segfault in QuantizedMatMul
Impact
If QuantizedMatMul is given nonscalar input for:
min_a
max_a
min_b
max_b
It gives a segfault that can be used to trigger a denial of service attack.
import tensorflow as tf Toutput = tf.qint32 transpose_a = False transpose_b = False Tactivation = tf.quint8 a = tf.constant(7, shape=[3,4], dtype=tf.quint8) b = tf.constant(1, shape=[2,3], dtype=tf.quint8)...
Patches
We have patched the issue in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48.
The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.
For more information
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Attribution
This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.
Mitigation
Update Impact
Minimal update. May introduce new vulnerabilities or breaking changes.
Ecosystem | Component | Affected version | Patched versions |
|---|---|---|---|
 pypi | 2.7.2, 2.8.1, 2.9.1 | ||
pypi | 2.7.2, 2.8.1, 2.9.1 | ||
pypi | 2.7.2, 2.8.1, 2.9.1 |
Aliases
References