GHSA-HRG5-737C-2P56
Vulnerability from github – Published: 2022-05-24 22:08 – Updated: 2022-05-24 22:08Impact
The implementation of tf.raw_ops.UnsortedSegmentJoin does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:
import tensorflow as tf
tf.raw_ops.UnsortedSegmentJoin(
inputs=tf.constant("this", shape=[12], dtype=tf.string),
segment_ids=tf.constant(0, shape=[12], dtype=tf.int64),
num_segments=tf.constant(0, shape=[12], dtype=tf.int64))
The code assumes num_segments is a scalar but there is no validation for this before accessing its value:
const Tensor& num_segments_tensor = context->input(2);
OP_REQUIRES(context, num_segments_tensor.NumElements() != 0,
errors::InvalidArgument("Number of segments cannot be empty."));
auto num_segments = num_segments_tensor.scalar<NUM_SEGMENTS_TYPE>()();
Patches
We have patched the issue in GitHub commit 13d38a07ce9143e044aa737cfd7bb759d0e9b400.
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
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"fixed": "2.6.4"
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"type": "ECOSYSTEM"
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{
"fixed": "2.8.1"
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{
"package": {
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"name": "tensorflow-cpu"
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{
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{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
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{
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{
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{
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},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.7.0"
},
{
"fixed": "2.7.2"
}
],
"type": "ECOSYSTEM"
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]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.8.0"
},
{
"fixed": "2.8.1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2022-29197"
],
"database_specific": {
"cwe_ids": [
"CWE-20"
],
"github_reviewed": true,
"github_reviewed_at": "2022-05-24T22:08:20Z",
"nvd_published_at": "2022-05-20T22:16:00Z",
"severity": "MODERATE"
},
"details": "### Impact\nThe implementation of [`tf.raw_ops.UnsortedSegmentJoin`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/unsorted_segment_join_op.cc#L92-L95) does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack:\n\n```python\nimport tensorflow as tf\n\ntf.raw_ops.UnsortedSegmentJoin(\n inputs=tf.constant(\"this\", shape=[12], dtype=tf.string),\n segment_ids=tf.constant(0, shape=[12], dtype=tf.int64),\n num_segments=tf.constant(0, shape=[12], dtype=tf.int64))\n``` \n \nThe code assumes `num_segments` is a scalar but there is no validation for this before accessing its value:\n\n```cc\nconst Tensor\u0026 num_segments_tensor = context-\u003einput(2);\nOP_REQUIRES(context, num_segments_tensor.NumElements() != 0,\n errors::InvalidArgument(\"Number of segments cannot be empty.\"));\nauto num_segments = num_segments_tensor.scalar\u003cNUM_SEGMENTS_TYPE\u003e()();\n``` \n\n### Patches\nWe have patched the issue in GitHub commit [13d38a07ce9143e044aa737cfd7bb759d0e9b400](https://github.com/tensorflow/tensorflow/commit/13d38a07ce9143e044aa737cfd7bb759d0e9b400).\n\nThe fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.\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### Attribution\nThis vulnerability has been reported by Neophytos Christou from Secure Systems Lab at Brown University.\n",
"id": "GHSA-hrg5-737c-2p56",
"modified": "2022-05-24T22:08:20Z",
"published": "2022-05-24T22:08:20Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hrg5-737c-2p56"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-29197"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/13d38a07ce9143e044aa737cfd7bb759d0e9b400"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/unsorted_segment_join_op.cc#L92-L95"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "Missing validation causes denial of service via `UnsortedSegmentJoin`"
}
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.