PYSEC-2021-212
Vulnerability from pysec - Published: 2021-05-14 20:15 - Updated: 2021-08-27 03:22
VLAI?
Details
TensorFlow is an end-to-end open source platform for machine learning. The implementation of tf.raw_ops.ReverseSequence allows for stack overflow and/or CHECK-fail based denial of service. The implementation(https://github.com/tensorflow/tensorflow/blob/5b3b071975e01f0d250c928b2a8f901cd53b90a7/tensorflow/core/kernels/reverse_sequence_op.cc#L114-L118) fails to validate that seq_dim and batch_dim arguments are valid. Negative values for seq_dim can result in stack overflow or CHECK-failure, depending on the version of Eigen code used to implement the operation. Similar behavior can be exhibited by invalid values of batch_dim. 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 | pkg:pypi/tensorflow |
|---|
Aliases
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow",
"purl": "pkg:pypi/tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "ecf768cbe50cedc0a45ce1ee223146a3d3d26d23"
}
],
"repo": "https://github.com/tensorflow/tensorflow",
"type": "GIT"
},
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.2.0rc0"
},
{
"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",
"2.1.4",
"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-2021-29575",
"GHSA-6qgm-fv6v-rfpv"
],
"details": "TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.ReverseSequence` allows for stack overflow and/or `CHECK`-fail based denial of service. The implementation(https://github.com/tensorflow/tensorflow/blob/5b3b071975e01f0d250c928b2a8f901cd53b90a7/tensorflow/core/kernels/reverse_sequence_op.cc#L114-L118) fails to validate that `seq_dim` and `batch_dim` arguments are valid. Negative values for `seq_dim` can result in stack overflow or `CHECK`-failure, depending on the version of Eigen code used to implement the operation. Similar behavior can be exhibited by invalid values of `batch_dim`. 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-2021-212",
"modified": "2021-08-27T03:22:34.716646Z",
"published": "2021-05-14T20:15:00Z",
"references": [
{
"type": "ADVISORY",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6qgm-fv6v-rfpv"
},
{
"type": "FIX",
"url": "https://github.com/tensorflow/tensorflow/commit/ecf768cbe50cedc0a45ce1ee223146a3d3d26d23"
}
]
}
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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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