PII leakage detection and monitor

The PII Leakage Detection solution provides enterprise-grade monitoring and analysis of machine learning model outputs to identify potential exposure of sensitive personal information. Using the highly efficient Aho-Corasick pattern matching algorithm, this tool systematically scans model responses for over 50 categories of Personally Identifiable Information (PII), including names, addresses, social security numbers, credit card information, and other sensitive data points. The solution delivers comprehensive reporting through multiple formats. JSON output files provide detailed technical analysis of detected leakages, including exact matches, context, and statistical breakdowns by PII category. The automated PDF report generation feature creates executive-friendly summaries with visualizations and risk assessments, making it easy to share findings with stakeholders and compliance teams. All results are organized in a clear directory structure for easy access and archival. Perfect for ML engineers, data scientists, and privacy officers, this tool integrates seamlessly into existing ML pipelines and testing workflows. Whether you're conducting pre-deployment safety validations, performing routine privacy audits, or responding to compliance requirements, this solution provides the robust PII detection capabilities needed to maintain data privacy standards and protect sensitive information in machine learning, Large Language Model (LLM) applications. We also included a Github repo for quick start instruction and test data https://github.com/Secludy/PII-inject-detect-tool