CVE-2022-41898: 
Python vulnerability analysis and mitigation

TensorFlow, an open source platform for machine learning, was found to contain a vulnerability (CVE-2022-41898) where if SparseFillEmptyRowsGrad is given empty inputs, it would cause the application to crash. This vulnerability was discovered by Jiawei Liu, a PhD student at University of Illinois, Urbana-Champaign, and affects versions prior to 2.11.0 (GitHub Advisory).

The vulnerability exists in the SparseFillEmptyRowsGrad operation when processing empty inputs. The issue can be triggered by calling the operation with empty reverseindexmap and grad_values parameters. The vulnerability has been assigned a CVSS score of 7.5 HIGH (NVD).

When exploited, this vulnerability causes TensorFlow to crash, resulting in a denial of service condition. This could affect applications and systems that rely on TensorFlow for machine learning operations, particularly those that process sparse tensors (GitHub Advisory).

The issue has been patched in GitHub commit af4a6a3c8b95022c351edae94560acc61253a1b8. The fix is included in TensorFlow 2.11.0, and has been backported to versions 2.10.1, 2.9.3, and 2.8.4. Users are advised to upgrade to these patched versions (GitHub Advisory).