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Universal Evasion Framework

A modular cybersecurity research framework that demonstrates polymorphic payload generation, fileless execution, AI-driven evasion, and dynamic C2 communication — designed for ethical use in controlled environments.

Project Overview

The Universal Evasion Framework showcases how modern adversarial techniques can bypass static detection using:

  • Polymorphic Payload Generation
  • AI-based Code Obfuscation
  • In-memory Execution (Fileless)
  • Simulated C2 Communication
  • Test Suite for Validation

This project is created for educational and research purposes only, especially for those exploring EDR/AV evasion techniques in ethical hacking and red teaming labs.

Module Breakdown

Module Description
payload_generator/generator.py Generates randomized Python payloads with unique signatures
payload_generator/payload.py Resulting payload: basic "print" with randomized string
memory_loader/loader.py Loads and executes payload directly from memory (fileless-style)
ai_evasion/adaptive_ai.py Obfuscates payload using simple AI-driven transformation
payload_generator/payload_ai.py Obfuscated payload generated from adaptive_ai.py
c2_manager/c2.py Simulates a basic C2 (Command & Control) connection using sockets
evaluation_suite/tester.py (Optional) Placeholder for automated detection bypass testing
tests/ Add your test scripts here

How to Run

Requirements: Python 3.x, netcat (nc), Linux environment

🔹 1. Generate a Polymorphic Payload

python3 payload_generator/generator.py

🔹 2. Run the Payload Normally

python3 payload_generator/payload.py

🔹 3. Run the Payload In-Memory (Fileless)

python3 memory_loader/loader.py

🔹 4. AI-Driven Payload Mutation

python3 ai_evasion/adaptive_ai.py
python3 payload_generator/payload_ai.py

🔹 5. Simulated C2 Communication

Start Listener (Attacker side):

nc -lvnp 4444

Connect from Client (Payload side):

python3 c2_manager/c2.py

Project Structure

universal-evasion-framework/
├── ai_evasion/
│   └── adaptive_ai.py
├── c2_manager/
│   └── c2.py
├── docs/
├── evaluation_suite/
│   └── tester.py
├── memory_loader/
│   └── loader.py
├── payload_generator/
│   ├── generator.py
│   ├── payload.py
│   └── payload_ai.py
├── tests/
└── README.md

Disclaimer

This project is strictly for educational and ethical research purposes only.

  • Do not use this framework on unauthorized systems or networks.
  • The developer is not responsible for any misuse, damage, or legal consequences.

By using this project, you agree to use it only in controlled environments for ethical purposes.

Contributing

Pull requests are welcome! For major changes, please open an issue first to discuss what you would like to change.

License

This project may be licensed under a custom license depending on distribution. Please check with the developer or maintainer before public use or redistribution.