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GHSA-452g-f7fp-9jf7

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

Описание

Type confusion during tensor casts lead to dereferencing null pointers

Impact

Calling TF operations with tensors of non-numeric types when the operations expect numeric tensors result in null pointer dereferences.

There are multiple ways to reproduce this, listing a few examples here:

import tensorflow as tf import numpy as np data = tf.random.truncated_normal(shape=1,mean=np.float32(20.8739),stddev=779.973,dtype=20,seed=64)
import tensorflow as tf import numpy as np data = tf.random.stateless_truncated_normal(shape=1,seed=[63,70],mean=np.float32(20.8739),stddev=779.973,dtype=20)
import tensorflow as tf import numpy as np data = tf.one_hot(indices=[62,50],depth=136,on_value=np.int32(237),off_value=158,axis=856,dtype=20)
import tensorflow as tf import numpy as np data = tf.range(start=np.int32(214),limit=660,delta=129,dtype=20)
import tensorflow as tf import numpy as np data = tf.raw_ops.ResourceCountUpTo(resource=np.int32(30), limit=872, T=3)
import tensorflow as tf import numpy as np writer_array = np.array([1,2],dtype=np.int32) writer_tensor = tf.convert_to_tensor(writer_array,dtype=tf.resource)

All these examples and similar ones have the same behavior: the conversion from Python array to C++ array is vulnerable to a type confusion:

int pyarray_type = PyArray_TYPE(array); PyArray_Descr* descr = PyArray_DESCR(array); switch (pyarray_type) { ... case NPY_VOID: // Quantized types are currently represented as custom struct types. // PyArray_TYPE returns NPY_VOID for structs, and we should look into // descr to derive the actual type. // Direct feeds of certain types of ResourceHandles are represented as a // custom struct type. return PyArrayDescr_to_TF_DataType(descr, out_tf_datatype); ... }

For the tensor types involved in the above example, the pyarray_type is NPY_VOID but the descr field is such that descr->field = NULL. Then PyArrayDescr_to_TF_DataType will trigger a null dereference:

Status PyArrayDescr_to_TF_DataType(PyArray_Descr* descr, TF_DataType* out_tf_datatype) { PyObject* key; PyObject* value; Py_ssize_t pos = 0; if (PyDict_Next(descr->fields, &pos, &key, &value)) { ... } }

This is because the Python's PyDict_Next implementation would dereference the first argument.

Patches

We have patched the issue in GitHub commit 030af767d357d1b4088c4a25c72cb3906abac489.

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 members of the Aivul Team from Qihoo 360 as well as Ye Zhang and Yakun Zhang 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: 3%
0.00017
Низкий

2 Low

CVSS4

2.5 Low

CVSS3

Дефекты

CWE-476

Связанные уязвимости

CVSS3: 2.5
nvd
больше 4 лет назад

TensorFlow is an end-to-end open source platform for machine learning. Calling TF operations with tensors of non-numeric types when the operations expect numeric tensors result in null pointer dereferences. The conversion from Python array to C++ array(https://github.com/tensorflow/tensorflow/blob/ff70c47a396ef1e3cb73c90513da4f5cb71bebba/tensorflow/python/lib/core/ndarray_tensor.cc#L113-L169) is vulnerable to a type confusion. 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: 3%
0.00017
Низкий

2 Low

CVSS4

2.5 Low

CVSS3

Дефекты

CWE-476