PYSEC-2021-242
Vulnerability from pysec - Published: 2021-05-14 20:15 - Updated: 2021-08-27 03:22TensorFlow is an end-to-end open source platform for machine learning. The TFLite code for allocating TFLiteIntArrays is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/4ceffae632721e52bf3501b736e4fe9d1221cdfa/tensorflow/lite/c/common.c#L24-L27). An attacker can craft a model such that the size multiplier is so large that the return value overflows the int datatype and becomes negative. In turn, this results in invalid value being given to malloc(https://github.com/tensorflow/tensorflow/blob/4ceffae632721e52bf3501b736e4fe9d1221cdfa/tensorflow/lite/c/common.c#L47-L52). In this case, ret->size would dereference an invalid pointer. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
| Name | purl | tensorflow | pkg:pypi/tensorflow |
|---|
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow",
"purl": "pkg:pypi/tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "7c8cc4ec69cd348e44ad6a2699057ca88faad3e5"
}
],
"repo": "https://github.com/tensorflow/tensorflow",
"type": "GIT"
},
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.1.4"
},
{
"introduced": "2.2.0"
},
{
"fixed": "2.2.3"
},
{
"introduced": "2.3.0"
},
{
"fixed": "2.3.3"
},
{
"introduced": "2.4.0"
},
{
"fixed": "2.4.2"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"0.12.0",
"0.12.0rc0",
"0.12.0rc1",
"0.12.1",
"1.0.0",
"1.0.1",
"1.1.0",
"1.1.0rc0",
"1.1.0rc1",
"1.1.0rc2",
"1.10.0",
"1.10.0rc0",
"1.10.0rc1",
"1.10.1",
"1.11.0",
"1.11.0rc0",
"1.11.0rc1",
"1.11.0rc2",
"1.12.0",
"1.12.0rc0",
"1.12.0rc1",
"1.12.0rc2",
"1.12.2",
"1.12.3",
"1.13.0rc0",
"1.13.0rc1",
"1.13.0rc2",
"1.13.1",
"1.13.2",
"1.14.0",
"1.14.0rc0",
"1.14.0rc1",
"1.15.0",
"1.15.0rc0",
"1.15.0rc1",
"1.15.0rc2",
"1.15.0rc3",
"1.15.2",
"1.15.3",
"1.15.4",
"1.15.5",
"1.2.0",
"1.2.0rc0",
"1.2.0rc1",
"1.2.0rc2",
"1.2.1",
"1.3.0",
"1.3.0rc0",
"1.3.0rc1",
"1.3.0rc2",
"1.4.0",
"1.4.0rc0",
"1.4.0rc1",
"1.4.1",
"1.5.0",
"1.5.0rc0",
"1.5.0rc1",
"1.5.1",
"1.6.0",
"1.6.0rc0",
"1.6.0rc1",
"1.7.0",
"1.7.0rc0",
"1.7.0rc1",
"1.7.1",
"1.8.0",
"1.8.0rc0",
"1.8.0rc1",
"1.9.0",
"1.9.0rc0",
"1.9.0rc1",
"1.9.0rc2",
"2.0.0",
"2.0.0a0",
"2.0.0b0",
"2.0.0b1",
"2.0.0rc0",
"2.0.0rc1",
"2.0.0rc2",
"2.0.1",
"2.0.2",
"2.0.3",
"2.0.4",
"2.1.0",
"2.1.0rc0",
"2.1.0rc1",
"2.1.0rc2",
"2.1.1",
"2.1.2",
"2.1.3",
"2.2.0",
"2.2.1",
"2.2.2",
"2.3.0",
"2.3.1",
"2.3.2",
"2.4.0",
"2.4.1"
]
}
],
"aliases": [
"CVE-2021-29605",
"GHSA-jf7h-7m85-w2v2"
],
"details": "TensorFlow is an end-to-end open source platform for machine learning. The TFLite code for allocating `TFLiteIntArray`s is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/4ceffae632721e52bf3501b736e4fe9d1221cdfa/tensorflow/lite/c/common.c#L24-L27). An attacker can craft a model such that the `size` multiplier is so large that the return value overflows the `int` datatype and becomes negative. In turn, this results in invalid value being given to `malloc`(https://github.com/tensorflow/tensorflow/blob/4ceffae632721e52bf3501b736e4fe9d1221cdfa/tensorflow/lite/c/common.c#L47-L52). In this case, `ret-\u003esize` would dereference an invalid pointer. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.",
"id": "PYSEC-2021-242",
"modified": "2021-08-27T03:22:40.058012Z",
"published": "2021-05-14T20:15:00Z",
"references": [
{
"type": "ADVISORY",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jf7h-7m85-w2v2"
},
{
"type": "FIX",
"url": "https://github.com/tensorflow/tensorflow/commit/7c8cc4ec69cd348e44ad6a2699057ca88faad3e5"
}
]
}
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.
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- 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.