GHSA-C582-C96P-R5CQ
Vulnerability from github – Published: 2022-02-10 00:20 – Updated: 2024-11-13 22:12
VLAI?
Summary
Memory exhaustion in Tensorflow
Details
Impact
The implementation of ThreadPoolHandle can be used to trigger a denial of service attack by allocating too much memory:
import tensorflow as tf
y = tf.raw_ops.ThreadPoolHandle(num_threads=0x60000000,display_name='tf')
This is because the num_threads argument is only checked to not be negative, but there is no upper bound on its value.
Patches
We have patched the issue in GitHub commit e3749a6d5d1e8d11806d4a2e9cc3123d1a90b75e.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Yu Tian of Qihoo 360 AIVul Team.
Severity ?
4.3 (Medium)
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.5.3"
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"type": "ECOSYSTEM"
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{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
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"events": [
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"introduced": "2.6.0"
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{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
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"introduced": "2.7.0"
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{
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"2.7.0"
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},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
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{
"events": [
{
"introduced": "0"
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{
"fixed": "2.5.3"
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{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
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"ranges": [
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"events": [
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"introduced": "2.6.0"
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{
"fixed": "2.6.3"
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{
"package": {
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"name": "tensorflow-cpu"
},
"ranges": [
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"events": [
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"introduced": "2.7.0"
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"fixed": "2.7.1"
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},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
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{
"package": {
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"name": "tensorflow-gpu"
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"events": [
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"introduced": "2.6.0"
},
{
"fixed": "2.6.3"
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"type": "ECOSYSTEM"
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]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.7.0"
},
{
"fixed": "2.7.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.7.0"
]
}
],
"aliases": [
"CVE-2022-21732"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2022-02-03T19:13:50Z",
"nvd_published_at": "2022-02-03T12:15:00Z",
"severity": "MODERATE"
},
"details": "### Impact \nThe [implementation of `ThreadPoolHandle`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/experimental/threadpool_dataset_op.cc#L79-L135) can be used to trigger a denial of service attack by allocating too much memory:\n\n```python\nimport tensorflow as tf\ny = tf.raw_ops.ThreadPoolHandle(num_threads=0x60000000,display_name=\u0027tf\u0027)\n```\n\nThis is because the `num_threads` argument is only checked to not be negative, but there is no upper bound on its value.\n \n### Patches\nWe have patched the issue in GitHub commit [e3749a6d5d1e8d11806d4a2e9cc3123d1a90b75e](https://github.com/tensorflow/tensorflow/commit/e3749a6d5d1e8d11806d4a2e9cc3123d1a90b75e).\n\nThe fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Yu Tian of Qihoo 360 AIVul Team.",
"id": "GHSA-c582-c96p-r5cq",
"modified": "2024-11-13T22:12:45Z",
"published": "2022-02-10T00:20:29Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c582-c96p-r5cq"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-21732"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/e3749a6d5d1e8d11806d4a2e9cc3123d1a90b75e"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-56.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-111.yaml"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/experimental/threadpool_dataset_op.cc#L79-L135"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Memory exhaustion 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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