{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
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{
"package": {
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{
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],
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}
]
},
{
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"name": "tensorflow-cpu"
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},
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"name": "tensorflow-gpu"
},
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],
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]
},
{
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"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
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],
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},
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"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
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"name": "tensorflow-gpu"
},
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"introduced": "2.4.0"
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}
],
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}
],
"aliases": [
"CVE-2021-29517"
],
"database_specific": {
"cwe_ids": [
"CWE-369"
],
"github_reviewed": true,
"github_reviewed_at": "2021-05-18T23:32:11Z",
"nvd_published_at": "2021-05-14T20:15:00Z",
"severity": "LOW"
},
"details": "### Impact\nA malicious user could trigger a division by 0 in `Conv3D` implementation:\n\n```python\nimport tensorflow as tf\n\ninput_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32)\nfilter_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32)\n\ntf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 56, 56, 1], padding=\u0027VALID\u0027, data_format=\u0027NDHWC\u0027, dilations=[1, 1, 1, 23, 1])\n```\n\nThe [implementation](https://github.com/tensorflow/tensorflow/blob/42033603003965bffac51ae171b51801565e002d/tensorflow/core/kernels/conv_ops_3d.cc#L143-L145) does a modulo operation based on user controlled input:\n\n```cc\n const int64 out_depth = filter.dim_size(4);\n OP_REQUIRES(context, in_depth % filter_depth == 0, ...);\n```\n\nThus, when `filter` has a 0 as the fifth element, this results in a division by 0.\n\nAdditionally, if the shape of the two tensors is not valid, an Eigen assertion can be triggered, resulting in a program crash:\n\n```python\nimport tensorflow as tf\n\ninput_tensor = tf.constant([], shape=[2, 2, 2, 2, 0], dtype=tf.float32)\nfilter_tensor = tf.constant([], shape=[0, 0, 2, 6, 2], dtype=tf.float32)\n\ntf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 39, 34, 1], padding=\u0027VALID\u0027, data_format=\u0027NDHWC\u0027, dilations=[1, 1, 1, 1, 1])\n```\n\nThe shape of the two tensors must follow the constraints specified in the [op description](https://www.tensorflow.org/api_docs/python/tf/raw_ops/Conv3D).\n\n### Patches\nWe have patched the issue in GitHub commit [799f835a3dfa00a4d852defa29b15841eea9d64f](https://github.com/tensorflow/tensorflow/commit/799f835a3dfa00a4d852defa29b15841eea9d64f).\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 Yakun Zhang and Ying Wang of Baidu X-Team.",
"id": "GHSA-772p-x54p-hjrv",
"modified": "2024-10-28T21:26:22Z",
"published": "2021-05-21T14:21:01Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-772p-x54p-hjrv"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29517"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/799f835a3dfa00a4d852defa29b15841eea9d64f"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-445.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-643.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-154.yaml"
}
],
"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": "Division by zero in `Conv3D`"
}