Safeguarding LLMs in Arabic Contexts
First comprehensive security evaluation dataset for Arabic language models
This research addresses a critical gap in LLM safety by developing a region-specific Arabic safety evaluation dataset with 5,799 questions across multiple threat categories.
- Includes direct attacks, indirect attacks, and harmless requests with sensitive words
- Adapted to reflect Arabic-specific socio-cultural contexts
- Provides essential benchmarks for evaluating Arabic LLM safety
- Highlights security vulnerabilities unique to Arabic linguistic features
This work is significant for security professionals as it enables proper assessment of LLM safety in Arabic contexts, helping prevent deployment of potentially harmful AI systems in Arabic-speaking regions.