Currently, when implementing data masking using regular expressions, we are facing performance issues due to the complexity and size of the expressions — especially when they contain a large number of words. This leads to system slowdowns or failures in masking operations.

We propose introducing clear guidelines or system-level recommendations on the optimal number of words that can be safely included in each regular expression without impacting performance.

Business Impact:

• Performance Optimization: Helps users design efficient masking rules that do not overload the system.
• Reduced Trial-and-Error: Saves time by avoiding repeated testing to find the right balance.
• Standardization Across Teams: Encourages consistent and scalable masking practices.
• Improved User Experience: Reduces frustration and improves reliability of data masking features.

Suggested Enhancement:

• Provide documentation or system feedback on regex complexity limits.
• Introduce a validation tool or warning system that flags overly complex expressions.
• Allow modular regex grouping or staged masking to handle large word sets more efficiently.