Access Audit

by mrachcore

Local user access audit dashboard built with Python and Streamlit.

Modern sysadmin-style tooling for CSV-based account reviews, risk detection and audit reporting.

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📌 Overview

Access Audit is a lightweight local dashboard designed to help review CSV-based user/account lists and identify potential access risks.

The application helps analyze uploaded account data, detect inactive or risky accounts, identify duplicate users, validate missing fields, and generate audit reports — all inside a clean modern dashboard interface.

This project was created as part of my learning journey during my Ausbildung as a Fachinformatiker für Systemintegration.

The application runs fully locally and does not require:

• cloud services
• paid APIs
• databases
• Docker
• external infrastructure
• Active Directory access

All analysis is performed locally on uploaded CSV files only.

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✨ Features

🖥 Dashboard

• Modern overview page
• Quick audit workflow explanation
• Professional internal-tool style UI
• Clean metric cards and navigation

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📂 Upload Data

• Upload CSV account lists
• Preview imported data
• Detect available columns
• Load included sample CSV
• Friendly validation messages

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🔎 Audit Checks

• Duplicate username detection
• Duplicate email detection
• Missing department detection
• Missing email detection
• Inactive account detection
• Admin account review
• Guest/external account detection
• Stale login analysis

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⚠ Risk Overview

• Simple risk scoring system

• Risk classification:

  • Low
  • Medium
  • High
  • Critical

• Top risky account overview

• Risk distribution summary

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📑 Reports

• Generate local audit reports
• TXT report export
• CSV export for risk tables
• Audit summaries and findings

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🛠 Tech Stack

Technology	Purpose
Python	Core language
Streamlit	Dashboard UI
pandas	CSV analysis
datetime	Login age checks
io	Export handling

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🎨 UI Design

The interface is inspired by:

• internal IT dashboards
• access review systems
• IAM/security audit tooling
• enterprise admin panels

Design Highlights

• Dark mode only
• Modern enterprise dashboard layout
• Soft cards and spacing
• Status badges
• Responsive tables
• Professional typography
• Subtle cyber-inspired accents
• Clean sidebar navigation

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🚀 Installation & Setup

Requirements

• Python 3.10 or newer recommended
• Local laptop or desktop
• Internet access only for installing Python packages

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Clone Repository

git clone https://github.com/mrachcore/access-audit.git

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Open Project Folder

cd access-audit

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Create Virtual Environment

python -m venv .venv

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Activate Virtual Environment

Windows

.venv\Scripts\activate

Linux/macOS

source .venv/bin/activate

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Install Dependencies

pip install -r requirements.txt

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▶ Run The App

streamlit run app.py

Streamlit will print a local URL, usually:

http://localhost:8501

Open that URL in your browser.

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📂 Project Structure

access-audit/
│
├── app.py
├── requirements.txt
├── README.md
│
├── assets/
│   └── logo.png
│
├── sample_data/
│   └── users_sample.csv
│
├── screenshots/
│   ├── dashboard.png
│   ├── upload-data.png
│   ├── audit-checks.png
│   ├── risk-overview.png
│   └── reports.png
│
└── utils/
    ├── audit_tools.py
    └── report_generator.py

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📸 Screenshots

Dashboard

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Upload Data

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Audit Checks

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Risk Overview

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Reports

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📄 Sample CSV

The project includes a sample CSV file:

sample_data/users_sample.csv

The file contains fictional example account data for testing and demonstration purposes.

Example columns:

• username
• email
• department
• role
• status
• last_login
• created_at

This allows the application to be tested immediately without real production data.

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🎯 Purpose of This Project

This project was built to:

• improve Python skills
• learn CSV and data analysis workflows
• practice audit-style logic
• understand access review concepts
• build realistic sysadmin tooling
• create a professional portfolio project

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📚 What I Learned

• CSV analysis with pandas
• Data validation
• Risk scoring systems
• Streamlit dashboard development
• Report generation
• Error handling
• Working with user/account datasets
• Building beginner-friendly tooling

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🔮 Future Improvements

Possible future additions:

• Excel (.xlsx) support
• JSON export
• More advanced risk scoring
• Account activity visualization
• Department-based filtering
• Search & filtering improvements
• Role permission templates
• PDF report export

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📝 Notes

• All analysis is performed locally.
• No uploaded data leaves the machine.
• The application does not connect to Active Directory or production systems.
• Invalid or missing CSV columns are handled gracefully where possible.
• Example data is fictional and intended only for testing.

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👨‍💻 Author

mrachcore

Code. Connect. Control.

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🌐 GitHub

Repository:

https://github.com/mrachcore/access-audit

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⚠ Disclaimer

This tool was created for educational and portfolio purposes.

Use responsibly and only with account data you are authorized to analyze.