CVE-2021-37644: 
Python vulnerability analysis and mitigation

TensorFlow, an end-to-end open source platform for machine learning, was found to have a vulnerability (CVE-2021-37644) where providing a negative element to the num_elements list argument of tf.raw_ops.TensorListReserve would cause the runtime to abort the process. This occurred due to an attempt to reallocate a std::vector with a negative number of elements. The vulnerability was discovered and disclosed in August 2021, affecting TensorFlow versions prior to 2.6.0 (GitHub Advisory).

The vulnerability stems from the implementation calling std::vector.resize() with a new size controlled by user input, without validating that this input is valid. When a negative value is provided to the num_elements parameter, it triggers a process abort due to invalid memory allocation attempt. The issue was present in the TensorFlow core kernels, specifically in the list_kernels.cc file (TensorFlow Commit).

When exploited, this vulnerability causes the runtime to abort the process, effectively creating a denial of service condition. The vulnerability could be triggered by any user with the ability to provide input to the TensorListReserve operation (GitHub Advisory).

The issue was patched in GitHub commit 8a6e874437670045e6c7dc6154c7412b4a2135e2 and included in TensorFlow 2.6.0. The fix was also backported to TensorFlow versions 2.5.1, 2.4.3, and 2.3.4. Users are recommended to upgrade to these patched versions to mitigate the vulnerability (GitHub Advisory).