ghsa-452g-f7fp-9jf7
Vulnerability from github
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:
python
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)
python
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)
python
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)
python
import tensorflow as tf
import numpy as np
data = tf.range(start=np.int32(214),limit=660,delta=129,dtype=20)
python
import tensorflow as tf
import numpy as np
data = tf.raw_ops.ResourceCountUpTo(resource=np.int32(30), limit=872, T=3)
```python 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:
cc
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:
cc
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.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
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"name": "tensorflow-cpu"
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{
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"name": "tensorflow-cpu"
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"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.3"
}
],
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},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
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"events": [
{
"introduced": "0"
},
{
"fixed": "2.1.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.3"
}
],
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},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.2"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2021-29513"
],
"database_specific": {
"cwe_ids": [
"CWE-476"
],
"github_reviewed": true,
"github_reviewed_at": "2021-05-18T23:42:09Z",
"nvd_published_at": "2021-05-14T20:15:00Z",
"severity": "LOW"
},
"details": "### Impact\nCalling TF operations with tensors of non-numeric types when the operations expect numeric tensors result in null pointer dereferences.\n\nThere are multiple ways to reproduce this, listing a few examples here:\n\n```python\nimport tensorflow as tf\nimport numpy as np\ndata = tf.random.truncated_normal(shape=1,mean=np.float32(20.8739),stddev=779.973,dtype=20,seed=64)\n```\n\n```python\nimport tensorflow as tf\nimport numpy as np\ndata =\ntf.random.stateless_truncated_normal(shape=1,seed=[63,70],mean=np.float32(20.8739),stddev=779.973,dtype=20)\n```\n\n```python\nimport tensorflow as tf\nimport numpy as np\ndata = tf.one_hot(indices=[62,50],depth=136,on_value=np.int32(237),off_value=158,axis=856,dtype=20)\n```\n\n```python\nimport tensorflow as tf\nimport numpy as np\ndata = tf.range(start=np.int32(214),limit=660,delta=129,dtype=20)\n```\n\n```python\nimport tensorflow as tf\nimport numpy as np\ndata = tf.raw_ops.ResourceCountUpTo(resource=np.int32(30), limit=872, T=3)\n```\n\n```python\nimport tensorflow as tf\nimport numpy as np\n\nwriter_array = np.array([1,2],dtype=np.int32)\nwriter_tensor = tf.convert_to_tensor(writer_array,dtype=tf.resource)\n```\n\nAll these examples and similar ones have the same behavior: 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:\n\n```cc\n int pyarray_type = PyArray_TYPE(array);\n PyArray_Descr* descr = PyArray_DESCR(array);\n switch (pyarray_type) {\n ...\n case NPY_VOID:\n // Quantized types are currently represented as custom struct types.\n // PyArray_TYPE returns NPY_VOID for structs, and we should look into\n // descr to derive the actual type.\n // Direct feeds of certain types of ResourceHandles are represented as a\n // custom struct type.\n return PyArrayDescr_to_TF_DataType(descr, out_tf_datatype);\n ...\n }\n```\n\nFor the tensor types involved in the above example, the `pyarray_type` is `NPY_VOID` but the `descr` field is such that `descr-\u003efield = NULL`. Then [`PyArrayDescr_to_TF_DataType`](https://github.com/tensorflow/tensorflow/blob/ff70c47a396ef1e3cb73c90513da4f5cb71bebba/tensorflow/python/lib/core/ndarray_tensor.cc#L72-L77) will trigger a null dereference:\n\n```cc\nStatus PyArrayDescr_to_TF_DataType(PyArray_Descr* descr,\n TF_DataType* out_tf_datatype) {\n PyObject* key;\n PyObject* value;\n Py_ssize_t pos = 0;\n if (PyDict_Next(descr-\u003efields, \u0026pos, \u0026key, \u0026value)) {\n ...\n }\n}\n```\n\nThis is because the Python\u0027s `PyDict_Next` implementation would dereference the first argument.\n\n### Patches\nWe have patched the issue in GitHub commit [030af767d357d1b4088c4a25c72cb3906abac489](https://github.com/tensorflow/tensorflow/commit/030af767d357d1b4088c4a25c72cb3906abac489).\n\nThe 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.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis 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.",
"id": "GHSA-452g-f7fp-9jf7",
"modified": "2024-10-30T23:13:43Z",
"published": "2021-05-21T14:20:46Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-452g-f7fp-9jf7"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29513"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/030af767d357d1b4088c4a25c72cb3906abac489"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-441.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-639.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-150.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Type confusion during tensor casts lead to dereferencing null pointers"
}
Sightings
| Author | Source | Type | Date |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or seen somewhere by the user.
- Confirmed: The vulnerability is confirmed from an analyst perspective.
- Exploited: This vulnerability was exploited and seen by the user reporting the sighting.
- Patched: This vulnerability was successfully patched by the user reporting the sighting.
- Not exploited: This vulnerability was not exploited or seen by the user reporting the sighting.
- Not confirmed: The user expresses doubt about the veracity of the vulnerability.
- Not patched: This vulnerability was not successfully patched by the user reporting the sighting.