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examples/basic_usage.py
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#!/usr/bin/env python3
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"""
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C2Sentinel Basic Usage Example
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Demonstrates loading the model and analyzing network connections
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for C2 beacon detection.
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"""
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from c2sentinel import C2Sentinel
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def main():
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# Load the model
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sentinel = C2Sentinel.load('c2_sentinel')
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# Example 1: Analyze a series of connections to a single destination
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# This pattern shows regular 60-second intervals with consistent packet sizes
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# - a common C2 beacon signature
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connections = []
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timestamp = 1705600000 # Starting timestamp
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for i in range(10):
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connections.append({
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'timestamp': timestamp + (i * 60), # 60-second intervals
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'dst_ip': '10.0.0.100',
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'dst_port': 443,
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'bytes_sent': 200,
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'bytes_recv': 500,
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})
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result = sentinel.analyze(connections)
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print("Example 1: Regular beacon pattern")
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print(f" Is C2: {result.is_c2}")
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print(f" Probability: {result.c2_probability:.2f}")
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print(f" C2 Type: {result.c2_type}")
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print(f" Detection Method: {result.detection_method}")
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print()
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# Example 2: Legitimate SSH keepalive traffic
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# Small symmetric packets on port 22 at regular intervals
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ssh_connections = []
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timestamp = 1705600000
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for i in range(10):
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ssh_connections.append({
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'timestamp': timestamp + (i * 30), # 30-second keepalive
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'dst_ip': '192.168.1.50',
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'dst_port': 22,
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'bytes_sent': 48,
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'bytes_recv': 48,
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})
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result = sentinel.analyze(ssh_connections)
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print("Example 2: SSH keepalive pattern")
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print(f" Is C2: {result.is_c2}")
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print(f" Matched Pattern: {result.matched_legitimate_pattern}")
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print(f" Service Type: {result.service_type}")
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print()
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# Example 3: High-confidence C2 on known malicious port
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c2_connections = []
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timestamp = 1705600000
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for i in range(10):
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c2_connections.append({
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'timestamp': timestamp + (i * 30),
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'dst_ip': '45.33.32.156',
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'dst_port': 4444, # Metasploit default
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'bytes_sent': 150,
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'bytes_recv': 300,
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})
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result = sentinel.analyze(c2_connections)
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print("Example 3: High-confidence C2 port")
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print(f" Is C2: {result.is_c2}")
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print(f" C2 Type: {result.c2_type}")
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print(f" Probability: {result.c2_probability:.2f}")
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print(f" Immediate Detection: {result.immediate_detection}")
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print(f" Risk Factors: {result.risk_factors}")
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print()
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# Example 4: Using threshold adjustment
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print("Example 4: Threshold adjustment")
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# Lower threshold for higher sensitivity
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result_low = sentinel.analyze(connections, threshold=0.3)
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print(f" Low threshold (0.3): is_c2={result_low.is_c2}, prob={result_low.c2_probability:.2f}")
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# Higher threshold for higher precision
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result_high = sentinel.analyze(connections, threshold=0.7)
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print(f" High threshold (0.7): is_c2={result_high.is_c2}, prob={result_high.c2_probability:.2f}")
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# Strict mode (minimum 0.7 threshold)
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result_strict = sentinel.analyze(connections, strict_mode=True)
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print(f" Strict mode: is_c2={result_strict.is_c2}, prob={result_strict.c2_probability:.2f}")
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if __name__ == '__main__':
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main()
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