GHSA-RJJG-HGV6-H69V
Vulnerability from github – Published: 2020-09-25 18:28 – Updated: 2024-10-28 20:17Impact
The implementation of dlpack.to_dlpack can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/python/tfe_wrapper.cc#L1361
However, there is nothing stopping users from passing in a Python object instead of a tensor.
In [2]: tf.experimental.dlpack.to_dlpack([2])
==1720623==WARNING: MemorySanitizer: use-of-uninitialized-value
#0 0x55b0ba5c410a in tensorflow::(anonymous namespace)::GetTensorFromHandle(TFE_TensorHandle*, TF_Status*) third_party/tensorflow/c/eager/dlpack.cc:46:7
#1 0x55b0ba5c38f4 in tensorflow::TFE_HandleToDLPack(TFE_TensorHandle*, TF_Status*) third_party/tensorflow/c/eager/dlpack.cc:252:26
...
The uninitialized memory address is due to a reinterpret_cast
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/python/eager/pywrap_tensor.cc#L848-L850
Since the PyObject is a Python object, not a TensorFlow Tensor, the cast to EagerTensor fails.
Patches
We have patched the issue in 22e07fb204386768e5bcbea563641ea11f96ceb8 and will release a patch release for all affected versions.
We recommend users to upgrade to TensorFlow 2.2.1 or 2.3.1.
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.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.2.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.3.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.2.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.3.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.2.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.3.0"
]
}
],
"aliases": [
"CVE-2020-15193"
],
"database_specific": {
"cwe_ids": [
"CWE-908"
],
"github_reviewed": true,
"github_reviewed_at": "2020-09-25T17:08:13Z",
"nvd_published_at": "2020-09-25T19:15:00Z",
"severity": "HIGH"
},
"details": "### Impact\nThe implementation of `dlpack.to_dlpack` can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor:\nhttps://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/python/tfe_wrapper.cc#L1361\n\nHowever, there is nothing stopping users from passing in a Python object instead of a tensor.\n```python\nIn [2]: tf.experimental.dlpack.to_dlpack([2]) \n==1720623==WARNING: MemorySanitizer: use-of-uninitialized-value \n #0 0x55b0ba5c410a in tensorflow::(anonymous namespace)::GetTensorFromHandle(TFE_TensorHandle*, TF_Status*) third_party/tensorflow/c/eager/dlpack.cc:46:7\n #1 0x55b0ba5c38f4 in tensorflow::TFE_HandleToDLPack(TFE_TensorHandle*, TF_Status*) third_party/tensorflow/c/eager/dlpack.cc:252:26\n... \n```\n\nThe uninitialized memory address is due to a `reinterpret_cast`\nhttps://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/python/eager/pywrap_tensor.cc#L848-L850\n\nSince the `PyObject` is a Python object, not a TensorFlow Tensor, the cast to `EagerTensor` fails. \n\n### Patches\nWe have patched the issue in 22e07fb204386768e5bcbea563641ea11f96ceb8 and will release a patch release for all affected versions.\n\nWe recommend users to upgrade to TensorFlow 2.2.1 or 2.3.1.\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-rjjg-hgv6-h69v",
"modified": "2024-10-28T20:17:48Z",
"published": "2020-09-25T18:28:27Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rjjg-hgv6-h69v"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2020-15193"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-273.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-308.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-116.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
},
{
"type": "WEB",
"url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:L",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:H/VA:L/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Memory corruption in Tensorflow"
}
Sightings
| Author | Source | Type | Date |
|---|
Nomenclature
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- Confirmed: The vulnerability has been validated from an analyst's perspective.
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- 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.