ghsa-cjc7-49v2-jp64
Vulnerability from github
5.8 (Medium) - CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:L/VA:H/SC:N/SI:N/SA:N
Impact
Incomplete validation in SparseAdd results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data:
```python import tensorflow as tf
a_indices = tf.zeros([10, 97], dtype=tf.int64) a_values = tf.zeros([10], dtype=tf.int64) a_shape = tf.zeros([0], dtype=tf.int64)
b_indices = tf.zeros([0, 0], dtype=tf.int64) b_values = tf.zeros([0], dtype=tf.int64) b_shape = tf.zeros([0], dtype=tf.int64)
thresh = 0
tf.raw_ops.SparseAdd(a_indices=a_indices, a_values=a_values, a_shape=a_shape, b_indices=b_indices, b_values=b_values, b_shape=b_shape, thresh=thresh) ```
The implementation has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of *_indices matches the size of corresponding *_shape. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation.
Patches
We have patched the issue in GitHub commit 6fd02f44810754ae7481838b6a67c5df7f909ca3 followed by GitHub commit 41727ff06111117bdf86b37db198217fd7a143cc.
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 Yakun Zhang and Ying Wang of Baidu X-Team.
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],
"aliases": [
"CVE-2021-29609"
],
"database_specific": {
"cwe_ids": [
"CWE-665",
"CWE-787"
],
"github_reviewed": true,
"github_reviewed_at": "2021-05-17T22:09:32Z",
"nvd_published_at": "2021-05-14T20:15:00Z",
"severity": "MODERATE"
},
"details": "### Impact\nIncomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data:\n\n```python\nimport tensorflow as tf\n\na_indices = tf.zeros([10, 97], dtype=tf.int64)\na_values = tf.zeros([10], dtype=tf.int64)\na_shape = tf.zeros([0], dtype=tf.int64)\n\nb_indices = tf.zeros([0, 0], dtype=tf.int64)\nb_values = tf.zeros([0], dtype=tf.int64)\nb_shape = tf.zeros([0], dtype=tf.int64)\n \nthresh = 0\n\ntf.raw_ops.SparseAdd(a_indices=a_indices,\n a_values=a_values,\n a_shape=a_shape,\n b_indices=b_indices,\n b_values=b_values,\n b_shape=b_shape,\n thresh=thresh)\n```\n\nThe [implementation](https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_add_op.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation.\n\n### Patches\nWe have patched the issue in GitHub commit [6fd02f44810754ae7481838b6a67c5df7f909ca3](https://github.com/tensorflow/tensorflow/commit/6fd02f44810754ae7481838b6a67c5df7f909ca3) followed by GitHub commit [41727ff06111117bdf86b37db198217fd7a143cc](https://github.com/tensorflow/tensorflow/commit/41727ff06111117bdf86b37db198217fd7a143cc).\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-cjc7-49v2-jp64",
"modified": "2024-11-13T16:19:57Z",
"published": "2021-05-21T14:28:29Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cjc7-49v2-jp64"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29609"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/41727ff06111117bdf86b37db198217fd7a143cc"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/6fd02f44810754ae7481838b6a67c5df7f909ca3"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-537.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-735.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-246.yaml"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:L/VA:H/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Incomplete validation in `SparseAdd`"
}
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.