CVE-2021-37660: 
Python vulnerability analysis and mitigation

TensorFlow, an end-to-end open source platform for machine learning, was found to contain a vulnerability (CVE-2021-37660) that allows attackers to trigger a floating point exception through inplace operations. The vulnerability was discovered in versions prior to 2.6.0 and disclosed on August 11, 2021. The affected versions include TensorFlow versions from 2.3.0 up to 2.6.0 (GitHub Advisory).

The vulnerability stems from a logic error in the implementation of inplace operations. The code incorrectly uses the OR operator (||) instead of AND operator (&&) when checking if tensors are empty, which should skip processing if both 'x' and 'v' are empty. This implementation flaw can be exploited by calling inplace operations with specially crafted arguments that result in a division by zero. The vulnerability can be demonstrated using the following code: tf.raw_ops.InplaceSub(x=[],i=[-99,-1,-1],v=[1,1,1]) (GitHub Advisory).

When successfully exploited, this vulnerability allows an attacker to cause a floating point exception in the application, potentially leading to application crashes and denial of service conditions (GitHub Advisory).

The vulnerability has been patched in multiple versions: TensorFlow 2.3.4, 2.4.3, 2.5.1, and 2.6.0. Users are recommended to upgrade to these patched versions. The fix involves correcting the logic operator in the implementation, as documented in commit e86605c0a336c088b638da02135ea6f9f6753618 (GitHub Advisory).