GHSA-5XWC-MRHX-5G3M
Vulnerability from github – Published: 2021-08-25 14:42 – Updated: 2024-11-13 20:52Impact
An attacker can cause undefined behavior via binding a reference to null pointer in all operations of type tf.raw_ops.MatrixDiagV*:
import tensorflow as tf
tf.raw_ops.MatrixDiagV3(
diagonal=[1,0],
k=[],
num_rows=[1,2,3],
num_cols=[4,5],
padding_value=[],
align='RIGHT_RIGHT')
The implementation has incomplete validation that the value of k is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong:
auto& diag_index = context->input(1);
...
lower_diag_index = diag_index.flat<int32>()(0);
Patches
We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09.
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.3.4"
}
],
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}
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},
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},
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{
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{
"package": {
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"name": "tensorflow"
},
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{
"introduced": "2.5.0"
},
{
"fixed": "2.5.1"
}
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}
],
"versions": [
"2.5.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
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{
"introduced": "0"
},
{
"fixed": "2.3.4"
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{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
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{
"events": [
{
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},
{
"fixed": "2.4.3"
}
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}
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{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.5.0"
},
{
"fixed": "2.5.1"
}
],
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}
],
"versions": [
"2.5.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.3.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.5.0"
},
{
"fixed": "2.5.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.5.0"
]
}
],
"aliases": [
"CVE-2021-37657"
],
"database_specific": {
"cwe_ids": [
"CWE-824"
],
"github_reviewed": true,
"github_reviewed_at": "2021-08-24T13:10:06Z",
"nvd_published_at": "2021-08-12T21:15:00Z",
"severity": "MODERATE"
},
"details": "### Impact\nAn attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`:\n\n```python\nimport tensorflow as tf\n\ntf.raw_ops.MatrixDiagV3(\n diagonal=[1,0],\n k=[],\n num_rows=[1,2,3],\n num_cols=[4,5],\n padding_value=[],\n align=\u0027RIGHT_RIGHT\u0027)\n``` \n\nThe [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong:\n\n```cc\n auto\u0026 diag_index = context-\u003einput(1);\n ...\n lower_diag_index = diag_index.flat\u003cint32\u003e()(0);\n```\n\n### Patches\nWe have patched the issue in GitHub commit [f2a673bd34f0d64b8e40a551ac78989d16daad09](https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09).\n\nThe fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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.",
"id": "GHSA-5xwc-mrhx-5g3m",
"modified": "2024-11-13T20:52:27Z",
"published": "2021-08-25T14:42:52Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5xwc-mrhx-5g3m"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-37657"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-570.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-768.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-279.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:H/VA:H/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Reference binding to nullptr in `MatrixDiagV*` ops"
}
Sightings
| Author | Source | Type | Date |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.