CVE-2021-29588: 
Python vulnerability analysis and mitigation

TensorFlow, an end-to-end open source platform for machine learning, was found to contain a vulnerability in the optimized implementation of the TransposeConv TFLite operator. The vulnerability (CVE-2021-29588) was discovered and reported by members of the Aivul Team from Qihoo 360, affecting TensorFlow versions prior to 2.5.0 (GitHub Advisory).

The vulnerability is a division by zero error in the optimized implementation of the TransposeConv TFLite operator. The issue occurs in the calculation of height_col and width_col values where stride_h and stride_w are used as divisors without proper validation. The vulnerable code performs calculations: height_col = (height + pad_t + pad_b - filter_h) / stride_h + 1 and width_col = (width + pad_l + pad_r - filter_w) / stride_w + 1 (GitHub Advisory).

When exploited, this vulnerability could cause a division by zero error, potentially leading to program crashes. The issue affects multiple versions of TensorFlow, including versions prior to 2.5.0, and specifically impacts versions 2.4.2, 2.3.3, 2.2.3, and 2.1.4 that were still in the supported range (GitHub Advisory).

An attacker can exploit this vulnerability by crafting a model where the stride_h and stride_w values are set to 0, triggering the division by zero error in the implementation (GitHub Advisory).

The vulnerability was patched in GitHub commit 801c1c6be5324219689c98e1bd3e0ca365ee834d and included in TensorFlow 2.5.0. The fix was also backported to TensorFlow versions 2.4.2, 2.3.3, 2.2.3, and 2.1.4. The patch implements validation checks to ensure that params->stride_height and params->stride_width are greater than 0 before performing the division (GitHub Commit).