CVE-2021-29540: 
Python vulnerability analysis and mitigation

TensorFlow, an open-source platform for machine learning, was found to contain a heap buffer overflow vulnerability (CVE-2021-29540) in its Conv2DBackpropFilter operation. The vulnerability was discovered in versions prior to 2.5.0 and affects all supported versions including 2.1.4, 2.2.3, 2.3.3, and 2.4.2 (TF Advisory).

The vulnerability stems from the implementation of Conv2DBackpropFilter where it computes the size of the filter tensor without validating that it matches the number of elements in filter_sizes. When reading or writing to this buffer, the code uses the computed value instead of the actual number of elements in the tensor, leading to potential heap buffer overflow (TF Advisory). The vulnerability has been assigned a CVSS v3.1 base score of 7.8 (HIGH) with vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H (NVD).

The vulnerability could allow an attacker to cause heap buffer overflow, potentially leading to memory corruption and unauthorized access to memory regions. This could result in high impacts on confidentiality, integrity, and availability of the affected system (NVD).

The vulnerability has been patched in TensorFlow 2.5.0. The fix has also been backported to TensorFlow versions 2.4.2, 2.3.3, 2.2.3, and 2.1.4. Users are advised to upgrade to these patched versions. The fix implements proper validation of the filter tensor size against the number of elements in filter_sizes (TF Advisory, TF Commit).