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Security Advisories: MDE2OlNlY3VyaXR5QWR2aXNvcnlHSFNBLTI0eDYtOGM3bS1odjNm

Heap OOB read in TFLite's implementation of `Minimum` or `Maximum`


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 indexes in both tensors with the same index but does not validate that the index is within bounds:

auto maxmin_func = [&](int indexes[N]) {
  output_data[SubscriptToIndex(output_desc, indexes)] =
    op(input1_data[SubscriptToIndex(desc1, indexes)],
        input2_data[SubscriptToIndex(desc2, indexes)]);


We have patched the issue in GitHub commit 953f28dca13c92839ba389c055587cfe6c723578.

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.

For more information

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This vulnerability has been reported by members of the Aivul Team from Qihoo 360.

Source: GitHub Advisory Database
Origin: Unspecified
Severity: Low
Classification: General
Published: about 2 years ago
Updated: 4 months ago

CVSS Score: 2.5
CVSS vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

Identifiers: GHSA-24x6-8c7m-hv3f, CVE-2021-29590

Affected Packages

Versions: >= 2.4.0, < 2.4.2, >= 2.3.0, < 2.3.3, >= 2.2.0, < 2.2.3, < 2.1.4
Fixed in: 2.4.2, 2.3.3, 2.2.3, 2.1.4