GHSA-W58W-79XV-6VCJ
Vulnerability from github – Published: 2022-11-21 20:39 – Updated: 2022-11-21 20:39
VLAI?
Summary
Out of bounds segmentation fault due to unequal op inputs in Tensorflow
Details
Impact
tf.raw_ops.DynamicStitch specifies input sizes when it is registered.
REGISTER_OP("DynamicStitch")
.Input("indices: N * int32")
.Input("data: N * T")
.Output("merged: T")
.Attr("N : int >= 1")
.Attr("T : type")
.SetShapeFn(DynamicStitchShapeFunction);
When it receives a differing number of inputs, such as when it is called with an indices size 1 and a data size 2, it will crash.
import tensorflow as tf
# indices = 1*[tf.random.uniform([1,2], dtype=tf.dtypes.int32, maxval=100)]
indices = [tf.constant([[0, 1]]),]
# data = 2*[tf.random.uniform([1,2], dtype=tf.dtypes.float32, maxval=100)]
data = [tf.constant([[5, 6]]), tf.constant([[7, 8]])]
tf.raw_ops.DynamicStitch(
indices=indices,
data=data)
Patches
We have patched the issue in GitHub commit f5381e0e10b5a61344109c1b7c174c68110f7629.
The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 as this is 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 Zizhuang Deng of IIE, UCAS
Severity ?
6.8 (Medium)
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.10.0"
},
{
"fixed": "2.10.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.10.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.10.0"
},
{
"fixed": "2.10.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.10.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.10.0"
},
{
"fixed": "2.10.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.10.0"
]
}
],
"aliases": [
"CVE-2022-41883"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": true,
"github_reviewed_at": "2022-11-21T20:39:20Z",
"nvd_published_at": "2022-11-18T21:15:00Z",
"severity": "MODERATE"
},
"details": "### Impact\n [`tf.raw_ops.DynamicStitch`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/dynamic_stitch_op.cc) specifies input sizes when it is [registered](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/data_flow_ops.cc). \n```cpp\nREGISTER_OP(\"DynamicStitch\")\n .Input(\"indices: N * int32\")\n .Input(\"data: N * T\")\n .Output(\"merged: T\")\n .Attr(\"N : int \u003e= 1\")\n .Attr(\"T : type\")\n .SetShapeFn(DynamicStitchShapeFunction);\n```\nWhen it receives a differing number of inputs, such as when it is called with an `indices` size 1 and a `data` size 2, it will crash.\n```python\nimport tensorflow as tf\n\n# indices = 1*[tf.random.uniform([1,2], dtype=tf.dtypes.int32, maxval=100)]\nindices = [tf.constant([[0, 1]]),]\n\n# data = 2*[tf.random.uniform([1,2], dtype=tf.dtypes.float32, maxval=100)]\ndata = [tf.constant([[5, 6]]), tf.constant([[7, 8]])]\n\ntf.raw_ops.DynamicStitch(\n indices=indices, \n data=data)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [f5381e0e10b5a61344109c1b7c174c68110f7629](https://github.com/tensorflow/tensorflow/commit/f5381e0e10b5a61344109c1b7c174c68110f7629).\n\nThe fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 as this is also affected.\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 Zizhuang Deng of IIE, UCAS\n",
"id": "GHSA-w58w-79xv-6vcj",
"modified": "2022-11-21T20:39:20Z",
"published": "2022-11-21T20:39:20Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w58w-79xv-6vcj"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-41883"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/f5381e0e10b5a61344109c1b7c174c68110f7629"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/dynamic_stitch_op.cc"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/data_flow_ops.cc"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:L/A:H",
"type": "CVSS_V3"
}
],
"summary": "Out of bounds segmentation fault due to unequal op inputs in Tensorflow"
}
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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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