
Arjun Krishna developed the Package Hallucination Data Toolkit for the NVIDIA/garak repository, focusing on synthetic dataset generation and enhanced detection of hallucinated package imports. He implemented cross-language pipelines in Python, JavaScript, and Ruby to fetch package creation data from npm, PyPI, and RubyGems, exporting results as TSV files for reproducible testing. His work included refining regular expressions for package reference detection, updating validation datasets, and introducing a cutoff-date filter to improve first-appearance criteria across languages. By integrating API data and scripting, Arjun enabled robust evaluation of hallucination detection, supporting research and improving security and import integrity verification workflows.

March 2025 monthly summary for NVIDIA/garak: Delivered the Package Hallucination Data Toolkit—dataset generation scripts across JavaScript, Python, and Ruby, plus detector enhancements. The work enables synthetic data testing and research, improves cross-language first-appearance detection, and strengthens end-to-end evaluation from data generation to detection, delivering measurable business value in security and import integrity verification.
March 2025 monthly summary for NVIDIA/garak: Delivered the Package Hallucination Data Toolkit—dataset generation scripts across JavaScript, Python, and Ruby, plus detector enhancements. The work enables synthetic data testing and research, improves cross-language first-appearance detection, and strengthens end-to-end evaluation from data generation to detection, delivering measurable business value in security and import integrity verification.
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