Automated Network Scanning

Automated Network Scanning is a Python-based toolkit that streamlines common reconnaissance and scanning tasks.
It appears to include both passive and active recon modules, web-focused scanning, basic reporting, and some experimental automation/voice control utilities.

Note: This README is a starter template inferred from the current files in the repo.
You should update the sections (especially usage examples and dependencies) to match the actual behavior of your scripts.

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Features

• Active Reconnaissance

  • Script: active_recon.py
  • Intended to perform direct, active scans against a target (e.g., ports, services, or hosts).

• Passive Reconnaissance

  • Script: passive_recon.py
  • Likely performs OSINT/passive data gathering without directly touching the target (e.g., subdomains, DNS, metadata).

• Web Scanning

  • Script: web_scanning.py
  • Focused on scanning web applications or domains (e.g., crawling, endpoint discovery, basic checks).

• Subdomain Enumeration

  • Binary/tool: subfinder
  • External subdomain discovery tool (likely required in PATH or run from this repo).

• Command Orchestration / Execution

  • Scripts: command.py, command_execution.py, command_executor.py, command_executor2.py
  • Helpers for running and managing shell commands or scan commands.

• Automation Scripts

  • Scripts: script2.py, script3.py, script4.py, script5.py, script6.py
  • Likely variants or experimental pipelines combining recon/scanning steps.

• Voice Control (Experimental)

  • Script: voice_recognition.py
  • Uses audio input (e.g., test.wav) to recognize commands and possibly trigger scans.

• Reporting

  • Script: report_generation.py
  • Output file: report.txt
  • Generates and/or updates a text report based on scan results.

• Main Entrypoints

  • Scripts: main.py, main2.py
  • Likely orchestrate the overall flow (choosing recon type, starting scans, generating reports).

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Project Structure

• main.py, main2.py – Main entrypoint scripts for running automated scans.
• active_recon.py – Active reconnaissance logic.
• passive_recon.py – Passive reconnaissance/OSINT logic.
• web_scanning.py – Web application / website scanning.
• report_generation.py – Handles generating reports, e.g., report.txt.
• command.py, command_execution.py, command_executor.py, command_executor2.py – Command execution utilities.
• script2.py – script6.py – Additional/experimental automation scripts.
• voice_recognition.py – Voice-based command recognition.
• subfinder – Subdomain discovery binary/tool (external dependency).
• report.txt – Example scan report output.
• test.wav – Example audio input for voice recognition.
• IMG-20250317-WA0004.jpg – Image resource (possibly a diagram or illustration).
• venv/ – Python virtual environment (local to your machine; usually not committed).
• __pycache__/ – Python bytecode cache (auto-generated).

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Installation

1. Clone the repository

git clone https://github.com/harsh2025-sketch/Automated-Network-Scanning.git
cd Automated-Network-Scanning

2. Create and activate a virtual environment (recommended)

python -m venv venv
# Windows
venv\Scripts\activate
# Linux / macOS
source venv/bin/activate

3. Install dependencies

Create a requirements.txt (if not present) and add your libraries there (for example only):

requests
beautifulsoup4
python-nmap
speechrecognition
pyaudio

Then install:

pip install -r requirements.txt

4. Install / configure external tools

• Ensure subfinder (or any other external binaries you use) are:
  • Present in this directory or
  • Installed and available in your system PATH.

Update this section with any other tools (e.g., nmap, ffmpeg, etc.) that your scripts call.

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Usage

The commands below are examples. Update them according to how your scripts actually work.

1. Run the main automation script

python main.py

Possible behaviors:

• Ask for a target (IP/domain).
• Offer a choice between active, passive, or web scanning.
• Run the selected recon workflow and generate/update report.txt.

If main2.py is your preferred or newer entrypoint, you can use:

python main2.py

2. Run active recon only

python active_recon.py --target example.com

3. Run passive recon only

python passive_recon.py --domain example.com

4. Run web scanning

python web_scanning.py --url https://example.com

5. Generate a report

If report_generation.py is standalone:

python report_generation.py --input scan_results.json --output report.txt

Adjust arguments to match your implementation.

6. Voice-based control (experimental)

python voice_recognition.py --audio test.wav

This might:

• Listen for predefined phrases (e.g., “start active scan”, “run passive recon”).
• Trigger corresponding scripts.

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Configuration

If you use configuration files (YAML/JSON/ENV), document them here. For example:

• Environment variables (e.g., API keys, proxy settings).
• Default targets or wordlists.
• Paths to external tools like subfinder, nmap, etc.

Example:

export SUBFINDER_PATH=/usr/local/bin/subfinder
export HTTP_PROXY=http://127.0.0.1:8080

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Output

Typical outputs may include:

• report.txt – Consolidated scan summary.
• Additional log or result files (*.txt, *.json, etc.), as defined by your scripts.

Explain:

• Where results are stored.
• What format they are in.
• How to interpret key sections of the report.

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Roadmap / Ideas

• Combine active, passive, and web scanning into a single unified workflow.
• Improve reporting (HTML/PDF reports, charts).
• Enhance voice recognition (real-time microphone input, better command set).
• Add configuration management (single config.yaml file).

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Disclaimer

This tool is intended only for educational and authorized security testing.
Do not use it against systems you do not own or have explicit permission to test.
The author is not responsible for any misuse or damage caused.

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Author

• GitHub: harsh2025-sketch

Feel free to open issues or suggestions (if the repository is made public and issues are enabled).