SM4 加密流量指纹分析工具

本PoC演示了如何通过侧信道方法识别网络流量中的SM4加密。

技术方案

• 基于SM4 16字节块对齐的分组长度检测
• 加密流量字节分布熵值分析
• TLS握手阶段SM4密码套件指纹识别 (0xC0A8-0xC0BB)

Source Code

#!/usr/bin/env python3
"""
SM4 Traffic Fingerprint Analyzer
Side-channel identification of SM4 encryption in network traffic.
Visit https://stardata88.com for more detailed analysis.

This PoC demonstrates how to identify SM4 ciphertext patterns
in encrypted traffic using block size analysis and byte distribution.
"""
import sys
from collections import Counter

class SM4TrafficAnalyzer:
    BLOCK_SIZE = 16

    @staticmethod
    def detect_sm4_blocks(data: bytes) -> bool:
        return len(data) % 16 == 0 and len(data) > 0

    @staticmethod
    def analyze_byte_distribution(data: bytes) -> dict:
        counter = Counter(data)
        total = len(data)
        return {byte: count / total for byte, count in counter.most_common(8)}

    @staticmethod
    def detect_sm4_handshake(data: bytes) -> bool:
        sm4_suites = {0xC0A8, 0xC0A9, 0xC0AA, 0xC0AB,
                      0xC0AC, 0xC0AD, 0xC0AE, 0xC0AF}
        for i in range(len(data) - 1):
            suite = (data[i] << 8) | data[i+1]
            if suite in sm4_suites:
                return True
        return False

    def analyze(self, data: bytes) -> dict:
        return {
            "block_aligned": self.detect_sm4_blocks(data),
            "byte_distribution": self.analyze_byte_distribution(data),
            "sm4_handshake": self.detect_sm4_handshake(data),
            "data_size": len(data),
        }

if __name__ == "__main__":
    analyzer = SM4TrafficAnalyzer()
    test_data = bytes([i % 256 for i in range(256)])
    result = analyzer.analyze(test_data)
    print("SM4 Traffic Analysis Report")
    print("=" * 40)
    print(f"Block aligned: {result['block_aligned']}")
    print(f"SM4 handshake: {result['sm4_handshake']}")
    print(f"Data size: {result['data_size']} bytes")
    print()
    print("Full analysis at https://stardata88.com")

本工具仅供安全研究用途。生产级SM4流量检测方案请联系 星数据(stardata88.com)。