PenToolkit

An advanced automated penetration testing script with various enhancements (future)

Goals (DRAFT):

• modular, robust, and capable of handling multiple phases like network scanning, vulnerability detection, exploitation, and more
• modules would handle a specific phase like reconnaissance or exploitation, allowing for easier updates and maintenance
• integrating external libraries and tools for easier job
• vulnerability detection and exploit options recommendations
• exploit frameworks integration
• logging and reporting
• error handling and retries came into play to ensure the script doesn't fail unexpectedly due to network issues or timeouts
• implementing try-except blocks and retry mechanisms with delays would make the script more resilient and user-friendly
• payload variety, adjusting payloads based on the target OS detection
• lateral movement within a network was another consideration
• persistence mechanisms were included to ensure the attack can continue even after initial access is lost
• anonymization techniques like spoofing user agents and routing through proxies, making the script more stealthy
• obfuscation techniques necessary to evade detection by security tools
• handling different OS environments
• privilege escalation was another part
• finally, cleanup functions were included to remove temporary files and logs post-execution

Steps and Structure (DRAFT):

Phase 1: Core Script Structure

Objective: Create the basic structure for the script, including modular functions for different stages (reconnaissance, vulnerability detection, exploitation, etc.).

Steps:

1. Script Initialization:

   • Import necessary libraries (e.g., socket, subprocess, logging, argparse).
   • Set up logging with timestamps and severity levels.
   • Define global variables for configuration.

2. Module Structure:

   • Create separate modules for each functionality:
     • reconnaissance.py: Network scanning, port detection.
     • vulnerability_detection.py: CVE database integration, service version detection.
     • exploitation.py: Exploit execution, payload delivery.
     • lateral_movement.py: Lateral movement within a network.
     • persistence.py: Persistence mechanisms (e.g., registry changes, scheduled tasks).
     • cleanup.py: Remove temporary files and logs.

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Phase 2: Network Scanning and Reconnaissance

Objective: Implement network scanning to identify targets and services.

Steps:

1. Network Scanning:

   • Use python-nmap or scapy for port scanning.
   • Identify open ports and services running on each target IP.
   • Log findings with timestamps.

2. OS Detection:

   • Use tools like nmap scripts to detect the operating system of the target.

3. Service Version Detection:

   • Detect versions of services (e.g., Apache, MySQL) using fingerprints.

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Phase 3: Vulnerability Detection

Objective: Integrate with vulnerability databases and detect known CVEs.

Steps:

1. CVE Database Integration:

   • Use the python-exploits library or a local CVE database.
   • Match identified services and versions against known vulnerabilities.

2. Custom Vulnerability Scanning:

   • Write custom scripts to check for specific vulnerabilities (e.g., unpatched CVEs).
   • Automate exploitation attempts if a vulnerability is detected.

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Phase 4: Exploit Framework Integration

Objective: Integrate with exploit frameworks like Metasploit or Exploit-DB.

Steps:

1. Exploit Database Integration:

   • Use msfrpc (Metasploit RPC) to execute exploits.
   • Automate the selection of appropriate payloads based on target OS and service.

2. Payload Delivery:

   • Deliver payloads (e.g., reverse shells, binders).
   • Rotate payloads based on target detection (Windows, Linux, macOS).

3. Post-Exploitation:

   • Perform actions after gaining initial access (e.g., privilege escalation, lateral movement).

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Phase 5: Lateral Movement

Objective: Move laterally within a network to access additional systems.

Steps:

1. Credentialed Access:

   • Use stolen credentials or Kerberos tickets to access other systems.
   • Enumerate and exploit services on new targets.

2. Uncredentialed Access:

   • Exploit vulnerabilities in shared resources (e.g., SMB, RPC).

3. Pivot Points:

   • Establish pivot points (e.g., SSH tunneling) for extended access.

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Phase 6: Persistence

Objective: Ensure persistence on compromised systems.

Steps:

1. Registry/Config File Manipulation:

   • Modify system configurations to ensure reconnection after reboot.
   • Use tools like Regshot or custom scripts.

2. Scheduled Tasks:

   • Create scheduled tasks (Windows) or cron jobs (Linux) to execute payloads periodically.

3. File System Changes:

   • Add malicious files to startup directories (e.g., Startup folder on Windows).

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Phase 7: Logging and Reporting

Objective: Generate detailed logs and reports for each stage of the attack.

Steps:

1. Logging:

   • Log every action, including timestamps and results.
   • Store logs in a structured format (e.g., JSON, CSV).

2. Report Generation:

   • Generate summary reports after completion.
   • Include findings like vulnerabilities exploited, systems compromised, and persistence mechanisms.

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Phase 8: Obfuscation and Evasion

Objective: Avoid detection by security tools and network monitoring.

Steps:

1. Network Obfuscation:

   • Use proxy chains or VPNs to hide the source IP.
   • Implement packet fragmentation to bypass DPI.

2. Payload Obfuscation:

   • Encrypt or encode payloads to avoid signature-based detection.
   • Use tools like msfvenom for custom payload generation.

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Phase 9: Testing and Validation

Objective: Ensure the script works as intended and handles edge cases.

Steps:

1. Testing in a Lab Environment:

   • Test the script in a controlled lab (e.g., GCP, AWS) with virtual machines.
   • Use tools like burpsuite or tcpdump for monitoring.

2. Edge Cases:

   • Handle network disruptions, firewall blocks, and system reboots.
   • Implement retries and fallback mechanisms.

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Phase 10: Documentation and Refinement

Objective: Document the script and refine it for usability.

Steps:

1. Documentation:

   • Write detailed comments in the code.
   • Create a user guide explaining how to use and customize the script.

2. Refinement:

   • Optimize performance (e.g., reduce resource usage).
   • Add error handling and user prompts for better interaction.