GHSA-hr84-fqvp-48mm
Vulnerability from github
Impact
Specifying a negative dense shape in tf.raw_ops.SparseCountSparseOutput results in a segmentation fault being thrown out from the standard library as std::vector invariants are broken.
```python import tensorflow as tf
indices = tf.constant([], shape=[0, 0], dtype=tf.int64) values = tf.constant([], shape=[0, 0], dtype=tf.int64) dense_shape = tf.constant([-100, -100, -100], shape=[3], dtype=tf.int64) weights = tf.constant([], shape=[0, 0], dtype=tf.int64)
tf.raw_ops.SparseCountSparseOutput(indices=indices, values=values, dense_shape=dense_shape, weights=weights, minlength=79, maxlength=96, binary_output=False) ```
This is because the implementation assumes the first element of the dense shape is always positive and uses it to initialize a BatchedMap<T> (i.e., std::vector<absl::flat_hash_map<int64,T>>) data structure.
cc
bool is_1d = shape.NumElements() == 1;
int num_batches = is_1d ? 1 : shape.flat<int64>()(0);
...
auto per_batch_counts = BatchedMap<W>(num_batches);
If the shape tensor has more than one element, num_batches is the first value in shape.
Ensuring that the dense_shape argument is a valid tensor shape (that is, all elements are non-negative) solves this issue.
Patches
We have patched the issue in GitHub commit c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3.
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.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.2"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2021-29521"
],
"database_specific": {
"cwe_ids": [
"CWE-131"
],
"github_reviewed": true,
"github_reviewed_at": "2021-05-18T23:23:47Z",
"nvd_published_at": "2021-05-14T20:15:00Z",
"severity": "LOW"
},
"details": "### Impact\nSpecifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken.\n\n```python\nimport tensorflow as tf\n\nindices = tf.constant([], shape=[0, 0], dtype=tf.int64)\nvalues = tf.constant([], shape=[0, 0], dtype=tf.int64)\ndense_shape = tf.constant([-100, -100, -100], shape=[3], dtype=tf.int64)\nweights = tf.constant([], shape=[0, 0], dtype=tf.int64)\n\ntf.raw_ops.SparseCountSparseOutput(indices=indices, values=values, dense_shape=dense_shape, weights=weights, minlength=79, maxlength=96, binary_output=False)\n```\n\nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap\u003cT\u003e` (i.e., [`std::vector\u003cabsl::flat_hash_map\u003cint64,T\u003e\u003e`](https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure.\n\n```cc\n bool is_1d = shape.NumElements() == 1;\n int num_batches = is_1d ? 1 : shape.flat\u003cint64\u003e()(0);\n ...\n auto per_batch_counts = BatchedMap\u003cW\u003e(num_batches); \n```\n\nIf the `shape` tensor has more than one element, `num_batches` is the first value in `shape`.\n \nEnsuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue.\n\n### Patches\nWe have patched the issue in GitHub commit [c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5](https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5).\n\nThe fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3.\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-hr84-fqvp-48mm",
"modified": "2024-10-28T21:21:03Z",
"published": "2021-05-21T14:21:16Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hr84-fqvp-48mm"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29521"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-449.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-647.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-158.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:N/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Segfault in SparseCountSparseOutput"
}
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.