
During December 2025, Arthan built the AI Safety Red Teaming Templates Library for the Azure/PyRIT repository, focusing on structured, scenario-based testing of AI safety controls. Leveraging skills in AI safety research, prompt engineering, and security testing, Arthan developed modular YAML templates that enable repeatable and extensible red-teaming exercises. The work included integrating a jailbreak template collection into PyRIT workflows, streamlining the setup for evaluating AI systems against safety bypass techniques. By contributing to documentation and usage guidelines, Arthan ensured the library’s adoption across safety and security teams, establishing a scalable foundation for risk assessment and governance alignment in AI environments.

December 2025: Delivered the AI Safety Red Teaming Templates Library for Azure/PyRIT to enable structured, scenario-based testing of AI safety controls. The feature provides a modular collection of templates to help evaluate AI systems against potential safety bypass techniques, improving risk assessment, governance alignment, and readiness for red-teaming engagements. This work establishes a scalable foundation for repeatable testing across environments and accelerates safe evaluation of AI safety measures.
December 2025: Delivered the AI Safety Red Teaming Templates Library for Azure/PyRIT to enable structured, scenario-based testing of AI safety controls. The feature provides a modular collection of templates to help evaluate AI systems against potential safety bypass techniques, improving risk assessment, governance alignment, and readiness for red-teaming engagements. This work establishes a scalable foundation for repeatable testing across environments and accelerates safe evaluation of AI safety measures.
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