GHSA-RH87-Q4VG-M45J
Vulnerability from github – Published: 2022-09-16 21:20 – Updated: 2022-09-16 21:20
VLAI?
Summary
TensorFlow vulnerable to integer overflow in math ops
Details
Impact
When RangeSize receives values that do not fit into an int64_t, it crashes.
auto size = (std::is_integral<T>::value
? ((Eigen::numext::abs(limit - start) +
Eigen::numext::abs(delta) - T(1)) /
Eigen::numext::abs(delta))
: (Eigen::numext::ceil(
Eigen::numext::abs((limit - start) / delta))));
// This check does not cover all cases.
if (size > std::numeric_limits<int64_t>::max()) {
return errors::InvalidArgument("Requires ((limit - start) / delta) <= ",
std::numeric_limits<int64_t>::max());
}
c->set_output(0, c->Vector(static_cast<int64_t>(size)));
return Status::OK();
}
Patches
We have patched the issue in GitHub commit 37e64539cd29fcfb814c4451152a60f5d107b0f0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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": "0"
},
{
"fixed": "2.7.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.8.0"
},
{
"fixed": "2.8.1"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.9.0"
},
{
"fixed": "2.9.1"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.7.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.8.0"
},
{
"fixed": "2.8.1"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.9.0"
},
{
"fixed": "2.9.1"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.7.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.8.0"
},
{
"fixed": "2.8.1"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.9.0"
},
{
"fixed": "2.9.1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2022-36015"
],
"database_specific": {
"cwe_ids": [
"CWE-190"
],
"github_reviewed": true,
"github_reviewed_at": "2022-09-16T21:20:28Z",
"nvd_published_at": "2022-09-16T23:15:00Z",
"severity": "LOW"
},
"details": "### Impact\nWhen [`RangeSize`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/math_ops.cc) receives values that do not fit into an `int64_t`, it crashes.\n```cpp\n auto size = (std::is_integral\u003cT\u003e::value\n ? ((Eigen::numext::abs(limit - start) +\n Eigen::numext::abs(delta) - T(1)) /\n Eigen::numext::abs(delta))\n : (Eigen::numext::ceil(\n Eigen::numext::abs((limit - start) / delta))));\n\n // This check does not cover all cases.\n if (size \u003e std::numeric_limits\u003cint64_t\u003e::max()) {\n return errors::InvalidArgument(\"Requires ((limit - start) / delta) \u003c= \",\n std::numeric_limits\u003cint64_t\u003e::max());\n }\n\n c-\u003eset_output(0, c-\u003eVector(static_cast\u003cint64_t\u003e(size)));\n return Status::OK();\n}\n```\n\n### Patches\nWe have patched the issue in GitHub commit [37e64539cd29fcfb814c4451152a60f5d107b0f0](https://github.com/tensorflow/tensorflow/commit/37e64539cd29fcfb814c4451152a60f5d107b0f0).\nThe fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.\n\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",
"id": "GHSA-rh87-q4vg-m45j",
"modified": "2022-09-16T21:20:28Z",
"published": "2022-09-16T21:20:28Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rh87-q4vg-m45j"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-36015"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/37e64539cd29fcfb814c4451152a60f5d107b0f0"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/math_ops.cc"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0"
}
],
"schema_version": "1.4.0",
"severity": [],
"summary": "TensorFlow vulnerable to integer overflow in math ops"
}
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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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