CVE-2021-29598: 
Python vulnerability analysis and mitigation

TensorFlow is an end-to-end open source platform for machine learning. The vulnerability (CVE-2021-29598) was identified in the implementation of the SVDF TFLite operator, which was found to be susceptible to a division by zero error. The issue was discovered by members of the Aivul Team from Qihoo 360 and was disclosed in May 2021 (TF Advisory).

The vulnerability exists in the SVDF TFLite operator implementation where a division operation is performed using the params->rank value without proper validation. The vulnerable code segment allows an attacker to craft a model where params->rank would be set to 0, leading to a division by zero error when executing num_filters % rank operation (TF Commit).

When successfully exploited, this vulnerability could lead to a denial of service condition in applications using the affected TensorFlow versions. The severity of this vulnerability was rated as Low according to the official assessment (TF Advisory).

An attacker can exploit this vulnerability by crafting a specific TensorFlow Lite model where the params->rank parameter is set to zero. This would trigger the division by zero error in the SVDF operator implementation (TF Advisory).

The vulnerability was patched in TensorFlow 2.5.0 and backported to versions 2.4.2, 2.3.3, 2.2.3, and 2.1.4. The fix involves adding a validation check to ensure that the rank parameter is not zero before performing the division operation (TF Advisory).