PYSEC-2021-696
Vulnerability from pysec - Published: 2021-05-14 20:15 - Updated: 2021-12-09 06:35
VLAI?
Details
TensorFlow is an end-to-end open source platform for machine learning. The implementation of tf.raw_ops.MaxPoolGradWithArgmax can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ef0c008ee84bad91ec6725ddc42091e19a30cf0e/tensorflow/core/kernels/maxpooling_op.cc#L1016-L1017) uses the same value to index in two different arrays but there is no guarantee that the sizes are identical. 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.
Impacted products
| Name | purl | tensorflow-gpu | pkg:pypi/tensorflow-gpu |
|---|
Aliases
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu",
"purl": "pkg:pypi/tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "dcd7867de0fea4b72a2b34bd41eb74548dc23886"
}
],
"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",
"0.12.1",
"1.0.0",
"1.0.1",
"1.1.0",
"1.10.0",
"1.10.1",
"1.11.0",
"1.12.0",
"1.12.2",
"1.12.3",
"1.13.1",
"1.13.2",
"1.14.0",
"1.15.0",
"1.15.2",
"1.15.3",
"1.15.4",
"1.15.5",
"1.2.0",
"1.2.1",
"1.3.0",
"1.4.0",
"1.4.1",
"1.5.0",
"1.5.1",
"1.6.0",
"1.7.0",
"1.7.1",
"1.8.0",
"1.9.0",
"2.0.0",
"2.0.1",
"2.0.2",
"2.0.3",
"2.0.4",
"2.1.0",
"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-2021-29570",
"GHSA-545v-42p7-98fq"
],
"details": "TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ef0c008ee84bad91ec6725ddc42091e19a30cf0e/tensorflow/core/kernels/maxpooling_op.cc#L1016-L1017) uses the same value to index in two different arrays but there is no guarantee that the sizes are identical. 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-2021-696",
"modified": "2021-12-09T06:35:26.840571Z",
"published": "2021-05-14T20:15:00Z",
"references": [
{
"type": "FIX",
"url": "https://github.com/tensorflow/tensorflow/commit/dcd7867de0fea4b72a2b34bd41eb74548dc23886"
},
{
"type": "ADVISORY",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-545v-42p7-98fq"
}
]
}
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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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