GHSA-cvgx-3v3q-m36c
Vulnerability from github
Impact
The shape inference code for QuantizeV2 can trigger a read outside of bounds of heap allocated array:
```python import tensorflow as tf
@tf.function def test(): data=tf.raw_ops.QuantizeV2( input=[1.0,1.0], min_range=[1.0,10.0], max_range=[1.0,10.0], T=tf.qint32, mode='MIN_COMBINED', round_mode='HALF_TO_EVEN', narrow_range=False, axis=-100, ensure_minimum_range=10) return data
test() ```
This occurs whenever axis is a negative value less than -1. In this case, we are accessing data before the start of a heap buffer:
cc
int axis = -1;
Status s = c->GetAttr("axis", &axis);
if (!s.ok() && s.code() != error::NOT_FOUND) {
return s;
}
...
if (axis != -1) {
...
TF_RETURN_IF_ERROR(
c->Merge(c->Dim(minmax, 0), c->Dim(input, axis), &depth));
}
The code allows axis to be an optional argument (s would contain an error::NOT_FOUND error code). Otherwise, it assumes that axis is a valid index into the dimensions of the input tensor. If axis is less than -1 then this results in a heap OOB read.
Patches
We have patched the issue in GitHub commit a0d64445116c43cf46a5666bd4eee28e7a82f244.
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.
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": "2.6.0"
},
{
"fixed": "2.6.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.6.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.6.0"
},
{
"fixed": "2.6.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.6.0"
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.6.0"
},
{
"fixed": "2.6.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.6.0"
]
}
],
"aliases": [
"CVE-2021-41211"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": true,
"github_reviewed_at": "2021-11-08T22:32:45Z",
"nvd_published_at": "2021-11-05T21:15:00Z",
"severity": "HIGH"
},
"details": "### Impact\nThe [shape inference code for `QuantizeV2`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/framework/common_shape_fns.cc#L2509-L2530) can trigger a read outside of bounds of heap allocated array:\n\n```python\nimport tensorflow as tf\n\n@tf.function\ndef test():\n data=tf.raw_ops.QuantizeV2(\n input=[1.0,1.0],\n min_range=[1.0,10.0],\n max_range=[1.0,10.0],\n T=tf.qint32,\n mode=\u0027MIN_COMBINED\u0027,\n round_mode=\u0027HALF_TO_EVEN\u0027,\n narrow_range=False,\n axis=-100,\n ensure_minimum_range=10)\n return data\n\ntest()\n```\n\nThis occurs whenever `axis` is a negative value less than `-1`. In this case, we are accessing data before the start of a heap buffer:\n \n```cc\nint axis = -1;\nStatus s = c-\u003eGetAttr(\"axis\", \u0026axis);\nif (!s.ok() \u0026\u0026 s.code() != error::NOT_FOUND) {\n return s;\n} \n... \nif (axis != -1) {\n ...\n TF_RETURN_IF_ERROR(\n c-\u003eMerge(c-\u003eDim(minmax, 0), c-\u003eDim(input, axis), \u0026depth));\n}\n```\n\nThe code allows `axis` to be an optional argument (`s` would contain an `error::NOT_FOUND` error code). Otherwise, it assumes that `axis` is a valid index into the dimensions of the `input` tensor. If `axis` is less than `-1` then this results in a heap OOB read.\n \n### Patches\nWe have patched the issue in GitHub commit [a0d64445116c43cf46a5666bd4eee28e7a82f244](https://github.com/tensorflow/tensorflow/commit/a0d64445116c43cf46a5666bd4eee28e7a82f244).\n \nThe fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.\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-cvgx-3v3q-m36c",
"modified": "2024-11-07T22:18:59Z",
"published": "2021-11-10T19:01:03Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cvgx-3v3q-m36c"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-41211"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/a0d64445116c43cf46a5666bd4eee28e7a82f244"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-620.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-818.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-403.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:H/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "Heap OOB in shape inference for `QuantizeV2`"
}
Sightings
| Author | Source | Type | Date |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or seen somewhere by the user.
- Confirmed: The vulnerability is confirmed from an analyst perspective.
- Exploited: This vulnerability was exploited and seen by the user reporting the sighting.
- Patched: This vulnerability was successfully patched by the user reporting the sighting.
- Not exploited: This vulnerability was not exploited or seen by the user reporting the sighting.
- Not confirmed: The user expresses doubt about the veracity of the vulnerability.
- Not patched: This vulnerability was not successfully patched by the user reporting the sighting.