GHSA-QG48-85HG-MQC5
Vulnerability from github – Published: 2021-05-21 14:23 – Updated: 2024-10-31 20:52Impact
An attacker can cause a denial of service via a FPE runtime error in tf.raw_ops.DenseCountSparseOutput:
import tensorflow as tf
values = tf.constant([], shape=[0, 0], dtype=tf.int64)
weights = tf.constant([])
tf.raw_ops.DenseCountSparseOutput(
values=values, weights=weights,
minlength=-1, maxlength=58, binary_output=True)
This is because the implementation computes a divisor value from user data but does not check that the result is 0 before doing the division:
int num_batch_elements = 1;
for (int i = 0; i < num_batch_dimensions; ++i) {
num_batch_elements *= data.shape().dim_size(i);
}
int num_value_elements = data.shape().num_elements() / num_batch_elements;
Since data is given by the values argument, num_batch_elements is 0.
Patches
We have patched the issue in GitHub commit da5ff2daf618591f64b2b62d9d9803951b945e9f.
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, as these are also affected.
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-2021-29554"
],
"database_specific": {
"cwe_ids": [
"CWE-369"
],
"github_reviewed": true,
"github_reviewed_at": "2021-05-18T20:58:24Z",
"nvd_published_at": "2021-05-14T19:15:00Z",
"severity": "LOW"
},
"details": "### Impact\nAn attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`:\n\n```python\nimport tensorflow as tf\n\nvalues = tf.constant([], shape=[0, 0], dtype=tf.int64)\nweights = tf.constant([])\n\ntf.raw_ops.DenseCountSparseOutput(\n values=values, weights=weights,\n minlength=-1, maxlength=58, binary_output=True)\n```\n \nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127) computes a divisor value from user data but does not check that the result is 0 before doing the division:\n\n```cc\nint num_batch_elements = 1;\nfor (int i = 0; i \u003c num_batch_dimensions; ++i) {\n num_batch_elements *= data.shape().dim_size(i);\n}\nint num_value_elements = data.shape().num_elements() / num_batch_elements;\n```\n\nSince `data` is given by the `values` argument, `num_batch_elements` is 0.\n\n### Patches\nWe have patched the issue in GitHub commit [da5ff2daf618591f64b2b62d9d9803951b945e9f](https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f).\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, as these are also affected.\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-qg48-85hg-mqc5",
"modified": "2024-10-31T20:52:11Z",
"published": "2021-05-21T14:23:55Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qg48-85hg-mqc5"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29554"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-482.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-680.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-191.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": "Division by 0 in `DenseCountSparseOutput`"
}
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.