CVE-2021-41198: 
Python vulnerability analysis and mitigation

TensorFlow, an open source platform for machine learning, was found to have a vulnerability (CVE-2021-41198) where calling tf.tile with large input arguments could cause the TensorFlow process to crash. The vulnerability was discovered in versions prior to 2.7.0 and was patched in versions 2.4.4, 2.5.2, and 2.6.1. The issue was first reported via a GitHub issue and later disclosed on November 5, 2021 (GitHub Advisory).

The vulnerability occurs when the number of elements in the output tensor exceeds the capacity of the int64_t type, leading to an overflow. This overflow is detected by a CHECK statement, which then causes the process to abort. The issue can be triggered by calling tf.tile with large multiplication factors, such as tf.keras.backend.tile(x=np.ones((1,1,1)), n=[100000000,100000000, 100000000]). The vulnerability has a CVSS v3.1 base score of 5.5 (Medium) with vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H (NVD).

When exploited, this vulnerability results in a crash of the TensorFlow process due to the CHECK-failure caused by the overflow. This can lead to denial of service conditions in applications utilizing the tf.tile functionality with large input parameters (GitHub Advisory).

The issue was patched in GitHub commit 9294094df6fea79271778eb7e7ae1bad8b5ef98f and included in TensorFlow version 2.7.0. The fix was also backported to versions 2.6.1, 2.5.2, and 2.4.4. Users are advised to upgrade to these patched versions to mitigate the vulnerability (GitHub Advisory).