193 privacy-meter(1) - Kailash Tool Reference
193.1 privacy-meter
privacy-meter - Privacy Meter — audits data privacy in statistical/ML models with membership-inference leakage metrics.
| Layer | ATTACK |
| Category | a-05-model-extraction-inversion |
| Safety class | requires-target |
| Licence | MIT |
| Upstream | github.com/privacytrustlab/ml_privacy_meter |
193.1.1 NAME
privacy-meter - Privacy Meter — audits data privacy in statistical/ML models with membership-inference leakage metrics.
193.1.2 SYNOPSIS & usage
Derived from the upstream README at generation time; verify against --help where the tool is installed.
pip install -r requirements.txtconda env create -f env.yaml193.1.3 DESCRIPTION (upstream)
Privacy Meter is an open-source library to audit data privacy in a wide range of statistical and machine learning algorithms (classification, regression, computer vision, and natural language processing). The tool enables data protection impact assessment based on the state-of-the-art membership inference attacks. Machine learning is playing a central role in automated decision-making in a wide range of organizations and service providers. The data, which are used to train the models, typically contain sensitive informat
193.1.4 CONFIGURATION (detected)
Config-surface markers detected in the upstream README (2 matches, e.g. env.yaml, env.yaml). A full config reference page for this tool is queued under the config-page policy — this line is the detection record, not the page.
193.1.5 SEE ALSO
- Category: a-05-model-extraction-inversion in the category directory (sister tools listed there).
ref: pin - verified 2026-10-14