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A three-headed guardian for the digital ecosystem. Cerberus-GPT is a modular AI framework designed to offer a complete and balanced view of cybersecurity, integrating analysis capabilities, attack simulation and defense recommendations in a single tool.
- Head 1: Analysis (The Watcher): Deeply analyzes code, networks, logs and data in search of vulnerabilities, anomalous patterns and potential risks. It uses natural language processing (NLP) and machine learning techniques to understand context and prioritize threats.
- Head 2: Attack Generation (The Attacker): Simulates a wide range of cyberattacks in an ethical and controlled manner. From social engineering and fuzzing to complex exploits, this head helps test the resilience of systems before a real attacker does.
- Head 3: Defense (The Guardian): Based on the findings of the other two heads, generate proactive defense strategies. It proposes patches, robust security configurations, firewall rules, and customized incident response plans.
- Modular Architecture: Each "head" can operate independently or together.
- Unified Interface: A single access point to control all functionalities.
- Advanced AI Engine: Powered by next-generation language models.
- Ethical Approach: Designed for offensive and defense in cybersecurity (ethical cybersecurity and "red teaming").
# Installation instructions coming soon...
git clone https://github.com/tu-usuario/Cerberus-GPT.git
cd Cerberus-GPT
pip install -r requirements.txt
## 🛠️ Quick Use
# Example of how to interact with heads
from cerberus_gpt import Cerberus
# Initialize the guardian
guardian = Cerberus()
# 1. Source code analysis
vulnerabilities = guardian.analyze_code('path/to/your/code.py')
print(vulnerabilities)
# 2. Simulate an attack on an IP
attack_report = guardian.simulate_attack('192.168.1.1', technique='sql_injection')
print(attack_report)
# 3. Defense recommendations
defense_plan = guardian.get_defense_plan(attack_report)
print(defense_plan)