> ## Documentation Index > Fetch the complete documentation index at: https://docs.specterops.io/llms.txt > Use this file to discover all available pages before exploring further. # Jupyter Notebooks Jupyter Lab environment for exploring Nemesis data through interactive notebooks with direct access to Hasura GraphQL and PostgreSQL. ## Overview The Jupyter service provides a powerful data analysis environment that allows you to: * Query Nemesis data using Hasura GraphQL * Perform advanced data analysis and visualization * Create custom investigations and reports * Explore file metadata, enrichment results, and security findings ## Access When Nemesis is running, Jupyter is available at: **URL**: `https://your-nemesis-host/jupyter/` Jupyter This is also linked to by the Nemesis `Help` menu. ## Authentication ### Environment Variable Password Use the `JUPYTER_PASSWORD` value in .env (or ENV variable) to log in. If this value is not set, you can discover the randomized value by running `docker compose logs jupyter | grep PASS` . ## Getting Started ### 1. Sample Notebooks The service comes with pre-configured sample notebooks: * **`1_getting_started.ipynb`**: Introduction to querying Nemesis data with examples * **`2_triage_false_positive_findings.ipynb`**: Marking findings with specific criteria as false positives ### 2. Pre-installed Libraries The Jupyter environment includes: * **Data Analysis**: pandas, numpy, matplotlib, seaborn, plotly * **GraphQL Client**: gql\[requests] for Hasura queries * **Database Access**: psycopg2-binary for direct PostgreSQL connections * **Utilities**: ipywidgets, python-dotenv ### 3. Environment Variables The following environment variables are automatically configured: * `HASURA_GRAPHQL_URL`: GraphQL endpoint (`http://hasura:8080/v1/graphql`) * `HASURA_ADMIN_SECRET`: Admin secret for Hasura access