PYSEC-2021-708
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. Due to lack of validation in tf.raw_ops.Dequantize, an attacker can trigger a read from outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/26003593aa94b1742f34dc22ce88a1e17776a67d/tensorflow/core/kernels/dequantize_op.cc#L106-L131) accesses the min_range and max_range tensors in parallel but fails to check that they have the same shape. 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": "5899741d0421391ca878da47907b1452f06aaf1b"
}
],
"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-2021-29582",
"GHSA-c45w-2wxr-pp53"
],
"details": "TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in `tf.raw_ops.Dequantize`, an attacker can trigger a read from outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/26003593aa94b1742f34dc22ce88a1e17776a67d/tensorflow/core/kernels/dequantize_op.cc#L106-L131) accesses the `min_range` and `max_range` tensors in parallel but fails to check that they have the same shape. 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-2021-708",
"modified": "2021-12-09T06:35:28.875018Z",
"published": "2021-05-14T20:15:00Z",
"references": [
{
"type": "FIX",
"url": "https://github.com/tensorflow/tensorflow/commit/5899741d0421391ca878da47907b1452f06aaf1b"
},
{
"type": "ADVISORY",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c45w-2wxr-pp53"
}
]
}
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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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