GHSA-J86V-P27C-73FM
Vulnerability from github – Published: 2021-11-10 19:17 – Updated: 2024-11-13 21:47Impact
During execution, EinsumHelper::ParseEquation() is supposed to set the flags in input_has_ellipsis vector and *output_has_ellipsis boolean to indicate whether there is ellipsis in the corresponding inputs and output.
However, the code only changes these flags to true and never assigns false.
for (int i = 0; i < num_inputs; ++i) {
input_label_counts->at(i).resize(num_labels);
for (const int label : input_labels->at(i)) {
if (label != kEllipsisLabel)
input_label_counts->at(i)[label] += 1;
else
input_has_ellipsis->at(i) = true;
}
}
output_label_counts->resize(num_labels);
for (const int label : *output_labels) {
if (label != kEllipsisLabel)
output_label_counts->at(label) += 1;
else
*output_has_ellipsis = true;
}
This results in unitialized variable access if callers assume that EinsumHelper::ParseEquation() always sets these flags.
Patches
We have patched the issue in GitHub commit f09caa532b6e1ac8d2aa61b7832c78c5b79300c6.
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.6.0"
},
{
"fixed": "2.6.1"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.5.0"
},
{
"fixed": "2.5.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.4.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.6.0"
},
{
"fixed": "2.6.1"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.5.0"
},
{
"fixed": "2.5.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.4.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.6.0"
},
{
"fixed": "2.6.1"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.5.0"
},
{
"fixed": "2.5.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.4.4"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2021-41201"
],
"database_specific": {
"cwe_ids": [
"CWE-824"
],
"github_reviewed": true,
"github_reviewed_at": "2021-11-08T22:49:15Z",
"nvd_published_at": "2021-11-05T20:15:00Z",
"severity": "HIGH"
},
"details": "### Impact\nDuring execution, [`EinsumHelper::ParseEquation()`](https://github.com/tensorflow/tensorflow/blob/e0b6e58c328059829c3eb968136f17aa72b6c876/tensorflow/core/kernels/linalg/einsum_op_impl.h#L126-L181) is supposed to set the flags in `input_has_ellipsis` vector and `*output_has_ellipsis` boolean to indicate whether there is ellipsis in the corresponding inputs and output.\n\nHowever, the code only changes these flags to `true` and never assigns `false`.\n\n```cc\nfor (int i = 0; i \u003c num_inputs; ++i) {\n input_label_counts-\u003eat(i).resize(num_labels);\n for (const int label : input_labels-\u003eat(i)) {\n if (label != kEllipsisLabel)\n input_label_counts-\u003eat(i)[label] += 1;\n else\n input_has_ellipsis-\u003eat(i) = true;\n }\n}\noutput_label_counts-\u003eresize(num_labels);\nfor (const int label : *output_labels) {\n if (label != kEllipsisLabel)\n output_label_counts-\u003eat(label) += 1;\n else\n *output_has_ellipsis = true;\n}\n```\n\nThis results in unitialized variable access if callers assume that `EinsumHelper::ParseEquation()` always sets these flags.\n\n\n### Patches\nWe have patched the issue in GitHub commit [f09caa532b6e1ac8d2aa61b7832c78c5b79300c6](https://github.com/tensorflow/tensorflow/commit/f09caa532b6e1ac8d2aa61b7832c78c5b79300c6).\n\nThe fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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.",
"id": "GHSA-j86v-p27c-73fm",
"modified": "2024-11-13T21:47:42Z",
"published": "2021-11-10T19:17:43Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j86v-p27c-73fm"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-41201"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/f09caa532b6e1ac8d2aa61b7832c78c5b79300c6"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-611.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-809.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-394.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:H/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Unitialized access in `EinsumHelper::ParseEquation`"
}
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.