GHSA-F2W8-JW48-FR7J
Vulnerability from github – Published: 2022-11-21 21:54 – Updated: 2022-11-21 21:54
VLAI?
Summary
`FractionalMaxPoolGrad` Heap out of bounds read
Details
Impact
If FractionMaxPoolGrad is given outsize inputs row_pooling_sequence and col_pooling_sequence, TensorFlow will crash.
import tensorflow as tf
tf.raw_ops.FractionMaxPoolGrad(
orig_input = [[[[1, 1, 1, 1, 1]]]],
orig_output = [[[[1, 1, 1]]]],
out_backprop = [[[[3], [3], [6]]]],
row_pooling_sequence = [-0x4000000, 1, 1],
col_pooling_sequence = [-0x4000000, 1, 1],
overlapping = False
)
Patches
We have patched the issue in GitHub commit d71090c3e5ca325bdf4b02eb236cfb3ee823e927.
The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, 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 Vul AI.
Severity ?
4.8 (Medium)
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
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"events": [
{
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"fixed": "2.8.4"
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{
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"name": "tensorflow-gpu"
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"ranges": [
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"introduced": "2.10.0"
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],
"type": "ECOSYSTEM"
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}
],
"aliases": [
"CVE-2022-41897"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": true,
"github_reviewed_at": "2022-11-21T21:54:04Z",
"nvd_published_at": "2022-11-18T22:15:00Z",
"severity": "MODERATE"
},
"details": "### Impact\nIf [`FractionMaxPoolGrad`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/fractional_max_pool_op.cc) is given outsize inputs `row_pooling_sequence` and `col_pooling_sequence`, TensorFlow will crash.\n\n```python\nimport tensorflow as tf\ntf.raw_ops.FractionMaxPoolGrad(\n\torig_input = [[[[1, 1, 1, 1, 1]]]],\n orig_output = [[[[1, 1, 1]]]],\n out_backprop = [[[[3], [3], [6]]]],\n row_pooling_sequence = [-0x4000000, 1, 1], \n col_pooling_sequence = [-0x4000000, 1, 1], \n overlapping = False\n )\n```\n\n### Patches\nWe have patched the issue in GitHub commit [d71090c3e5ca325bdf4b02eb236cfb3ee823e927](https://github.com/tensorflow/tensorflow/commit/d71090c3e5ca325bdf4b02eb236cfb3ee823e927).\n\nThe fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, 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 Vul AI.\n",
"id": "GHSA-f2w8-jw48-fr7j",
"modified": "2022-11-21T21:54:04Z",
"published": "2022-11-21T21:54:04Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f2w8-jw48-fr7j"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-41897"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/d71090c3e5ca325bdf4b02eb236cfb3ee823e927"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/fractional_max_pool_op.cc"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "`FractionalMaxPoolGrad` Heap out of bounds read"
}
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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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