pysec-2021-168
Vulnerability from pysec
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a CHECK fail in PNG encoding by providing an empty input tensor as the pixel data. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L57-L60) only validates that the total number of pixels in the image does not overflow. Thus, an attacker can send an empty matrix for encoding. However, if the tensor is empty, then the associated buffer is nullptr. Hence, when calling png::WriteImageToBuffer(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L79-L93), the first argument (i.e., image.flat<T>().data()) is NULL. This then triggers the CHECK_NOTNULL in the first line of png::WriteImageToBuffer(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/lib/png/png_io.cc#L345-L349). Since image is null, this results in abort being called after printing the stacktrace. Effectively, this allows an attacker to mount a denial of service attack. 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.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow",
"purl": "pkg:pypi/tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "26eb323554ffccd173e8a79a8c05c15b685ae4d1"
}
],
"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-2021-29531",
"GHSA-3qxp-qjq7-w4hf"
],
"details": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a `CHECK` fail in PNG encoding by providing an empty input tensor as the pixel data. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L57-L60) only validates that the total number of pixels in the image does not overflow. Thus, an attacker can send an empty matrix for encoding. However, if the tensor is empty, then the associated buffer is `nullptr`. Hence, when calling `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L79-L93), the first argument (i.e., `image.flat\u003cT\u003e().data()`) is `NULL`. This then triggers the `CHECK_NOTNULL` in the first line of `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/lib/png/png_io.cc#L345-L349). Since `image` is null, this results in `abort` being called after printing the stacktrace. Effectively, this allows an attacker to mount a denial of service attack. 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-2021-168",
"modified": "2021-08-27T03:22:26.851089Z",
"published": "2021-05-14T20:15:00Z",
"references": [
{
"type": "FIX",
"url": "https://github.com/tensorflow/tensorflow/commit/26eb323554ffccd173e8a79a8c05c15b685ae4d1"
},
{
"type": "ADVISORY",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3qxp-qjq7-w4hf"
}
]
}
Sightings
| Author | Source | Type | Date |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or seen somewhere by the user.
- Confirmed: The vulnerability is confirmed from an analyst perspective.
- Exploited: This vulnerability was exploited and seen by the user reporting the sighting.
- Patched: This vulnerability was successfully patched by the user reporting the sighting.
- Not exploited: This vulnerability was not exploited or seen by the user reporting the sighting.
- Not confirmed: The user expresses doubt about the veracity of the vulnerability.
- Not patched: This vulnerability was not successfully patched by the user reporting the sighting.