pysec-2021-716
Vulnerability from pysec
TensorFlow is an end-to-end open source platform for machine learning. The implementations of the Minimum
and Maximum
TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty. This is because the broadcasting implementation(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within bounds. 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-gpu", "purl": "pkg:pypi/tensorflow-gpu" }, "ranges": [ { "events": [ { "introduced": "0" }, { "fixed": "953f28dca13c92839ba389c055587cfe6c723578" } ], "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-2021-29590", "GHSA-24x6-8c7m-hv3f" ], "details": "TensorFlow is an end-to-end open source platform for machine learning. The implementations of the `Minimum` and `Maximum` TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty. This is because the broadcasting implementation(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within bounds. 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-2021-716", "modified": "2021-12-09T06:35:30.403366Z", "published": "2021-05-14T20:15:00Z", "references": [ { "type": "FIX", "url": "https://github.com/tensorflow/tensorflow/commit/953f28dca13c92839ba389c055587cfe6c723578" }, { "type": "ADVISORY", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-24x6-8c7m-hv3f" } ] }
Sightings
Author | Source | Type | Date |
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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.