{"repo":"nithin42/privacylens","free":true,"listed":false,"github":"https://github.com/nithin42/privacylens","clone":"git clone https://github.com/nithin42/privacylens.git","description":"Open-source Python library to audit ML pipelines for privacy vulnerabilities - MIA, PII leakage, model inversion","language":"Python","stars":32,"topics":["ai-security","azureml","differential-privacy","gdpr","llm-audit","machine-learning","mlops","privacy","python","security"],"license":"MIT","category":"security-tools","readme_excerpt":"🔍 privacylens Audit any ML model for privacy vulnerabilities — in 3 lines of code. 📦 PyPI Installation Note : The PyPI package for privacylens is published as privacyaudit . Install via pip: pip install privacyaudit (or pip install \"privacyaudit[azure]\" ). --- 💡 Abstract (Executive Summary) The Problem : When Machine Learning models are trained on private data (like medical records, financial transactions, or customer emails), they can accidentally memorize that sensitive information. Attackers can then extract private data or determine if a specific person's record was in the training set. The Solution : privacylens is an open-source privacy auditing toolkit. In 3 lines of code , it runs 5 automated security checks against any ML model (scikit-learn, PyTorch, XGBoost, HuggingFace) to detect data leakage risks before deployment. Why it matters : - 🧑‍💻 For Developers : Catch privacy bugs automatically in CI/CD pipelines before pushing models to production. - 🏢 For Enterprises : Generate standalone interactive HTML compliance reports for GDPR and HIPAA audits. --- 🎯 What is privacylens? Most ML engineers don't know if their model is leaking private training data . privacylens audits it across 5 core privacy vulnerability vectors. --- ✨ 5-Point Privacy Audit Suite - 🕵️ 1. Membership Inference Attack (MIA) — Detect if an attacker can identify training records using shadow model estimation (Shokri et al., 2017) - 🔎 2. PII Leakage Detection — Scan predictions and samples f","default_branch":null,"files":null,"tree":[],"storefront":"/r/nithin42","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/nithin42/privacylens/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}