Abstract
This describes novel methods for rotating AI-generated code canaries to improve the resilience and effectiveness of source code leak detection. We introduce three distinct rotation strategies: simple rotation, dynamic rotation triggered by code changes, and algorithmic rotation using pseudorandom sequences. These methods enhance security by making it significantly more difficult for attackers to detect and neutralize canaries, thereby increasing the likelihood of early leak detection.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Van Hoose, Ray, "AI-Powered Canary Rotation for Enhanced Source Code Leak Detection", Technical Disclosure Commons, (December 31, 2024)
https://www.tdcommons.org/dpubs_series/7692
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