GHSA-GF88-J2MG-CC82
Vulnerability from github – Published: 2021-08-25 14:42 – Updated: 2024-11-13 20:54
VLAI?
Summary
Crash caused by integer conversion to unsigned
Details
Impact
An attacker can cause a denial of service in boosted_trees_create_quantile_stream_resource by using negative arguments:
import tensorflow as tf
from tensorflow.python.ops import gen_boosted_trees_ops
import numpy as np
v= tf.Variable([0.0, 0.0, 0.0, 0.0, 0.0])
gen_boosted_trees_ops.boosted_trees_create_quantile_stream_resource(
quantile_stream_resource_handle = v.handle,
epsilon = [74.82224],
num_streams = [-49],
max_elements = np.int32(586))
The implementation does not validate that num_streams only contains non-negative numbers. In turn, this results in using this value to allocate memory:
class BoostedTreesQuantileStreamResource : public ResourceBase {
public:
BoostedTreesQuantileStreamResource(const float epsilon,
const int64 max_elements,
const int64 num_streams)
: are_buckets_ready_(false),
epsilon_(epsilon),
num_streams_(num_streams),
max_elements_(max_elements) {
streams_.reserve(num_streams_);
...
}
}
However, reserve receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library.
Patches
We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992.
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 members of the Aivul Team from Qihoo 360.
Severity ?
5.5 (Medium)
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.3.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.5.0"
},
{
"fixed": "2.5.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.5.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.3.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.5.0"
},
{
"fixed": "2.5.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.5.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.3.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.3"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.5.0"
},
{
"fixed": "2.5.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.5.0"
]
}
],
"aliases": [
"CVE-2021-37661"
],
"database_specific": {
"cwe_ids": [
"CWE-681"
],
"github_reviewed": true,
"github_reviewed_at": "2021-08-24T13:23:52Z",
"nvd_published_at": "2021-08-12T21:15:00Z",
"severity": "MODERATE"
},
"details": "### Impact\nAn attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments:\n\n```python\nimport tensorflow as tf\nfrom tensorflow.python.ops import gen_boosted_trees_ops\nimport numpy as np\n\nv= tf.Variable([0.0, 0.0, 0.0, 0.0, 0.0])\ngen_boosted_trees_ops.boosted_trees_create_quantile_stream_resource(\n quantile_stream_resource_handle = v.handle,\n epsilon = [74.82224],\n num_streams = [-49], \n max_elements = np.int32(586))\n```\n\nThe [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40):\n\n```cc\nclass BoostedTreesQuantileStreamResource : public ResourceBase {\n public:\n BoostedTreesQuantileStreamResource(const float epsilon,\n const int64 max_elements,\n const int64 num_streams)\n : are_buckets_ready_(false),\n epsilon_(epsilon),\n num_streams_(num_streams),\n max_elements_(max_elements) {\n streams_.reserve(num_streams_);\n ...\n }\n}\n```\n\nHowever, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library.\n\n### Patches\nWe have patched the issue in GitHub commit [8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992](https://github.com/tensorflow/tensorflow/commit/8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992).\n\nThe fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 members of the Aivul Team from Qihoo 360.",
"id": "GHSA-gf88-j2mg-cc82",
"modified": "2024-11-13T20:54:40Z",
"published": "2021-08-25T14:42:28Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gf88-j2mg-cc82"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-37661"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-574.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-772.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-283.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
}
],
"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"
},
{
"score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Crash caused by integer conversion to unsigned"
}
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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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