ghsa-fqxc-pvf8-2w9v
Vulnerability from github
Published
2022-09-16 22:09
Modified
2022-09-21 19:33
Severity ?
Summary
TensorFlow vulnerable to null dereference on MLIR on empty function attributes
Details
Impact
Eig can be fed an incorrect Tout input, resulting in a CHECK fail that can trigger a denial of service attack.
python
import tensorflow as tf
import numpy as np
arg_0=tf.constant(value=np.random.random(size=(2, 2)), shape=(2, 2), dtype=tf.float32)
arg_1=tf.complex128
arg_2=True
arg_3=''
tf.raw_ops.Eig(input=arg_0, Tout=arg_1, compute_v=arg_2, name=arg_3)
Patches
We have patched the issue in GitHub commit aed36912609fc07229b4d0a7b44f3f48efc00fd0.
The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.7.2"
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],
"type": "ECOSYSTEM"
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{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
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"package": {
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{
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"name": "tensorflow-cpu"
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"ranges": [
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{
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},
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"package": {
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"name": "tensorflow-gpu"
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"ranges": [
{
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{
"package": {
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"name": "tensorflow-gpu"
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"ranges": [
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{
"package": {
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"name": "tensorflow-gpu"
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"ranges": [
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"introduced": "2.9.0"
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{
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}
],
"type": "ECOSYSTEM"
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}
],
"aliases": [
"CVE-2022-36000"
],
"database_specific": {
"cwe_ids": [
"CWE-476"
],
"github_reviewed": true,
"github_reviewed_at": "2022-09-16T22:09:36Z",
"nvd_published_at": "2022-09-16T23:15:00Z",
"severity": "MODERATE"
},
"details": "### Impact\n`Eig` can be fed an incorrect `Tout` input, resulting in a `CHECK` fail that can trigger a denial of service attack.\n```python\nimport tensorflow as tf\nimport numpy as np \narg_0=tf.constant(value=np.random.random(size=(2, 2)), shape=(2, 2), dtype=tf.float32)\narg_1=tf.complex128\narg_2=True\narg_3=\u0027\u0027\ntf.raw_ops.Eig(input=arg_0, Tout=arg_1, compute_v=arg_2, name=arg_3)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [aed36912609fc07229b4d0a7b44f3f48efc00fd0](https://github.com/tensorflow/tensorflow/commit/aed36912609fc07229b4d0a7b44f3f48efc00fd0).\n\nThe fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.\n\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\n### Attribution\nThis vulnerability has been reported by \u5218\u529b\u6e90, Information System \u0026 Security and Countermeasures Experiments Center, Beijing Institute of Technology.\n",
"id": "GHSA-fqxc-pvf8-2w9v",
"modified": "2022-09-21T19:33:21Z",
"published": "2022-09-16T22:09:36Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fqxc-pvf8-2w9v"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-36000"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/aed36912609fc07229b4d0a7b44f3f48efc00fd0"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "TensorFlow vulnerable to null dereference on MLIR on empty function attributes"
}
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Sightings
| Author | Source | Type | Date |
|---|
Nomenclature
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