环境准备和配置
网络拓扑
手机设备 (APP) → WiFi路由器 → 电脑 (运行Wireshark)工具准备
# 安装Wireshark
# Windows: 从官网下载安装包
# Mac: brew install wireshark
# Linux: sudo apt-get install wireshark
# 安装adb工具（Android调试）
brew install android-platform-tools # Mac
# 或下载Android Studio包含的adb手机流量捕获方法
WiFi网络捕获（推荐）
设置电脑为热点
# Windows - 创建热点
netsh wlan set hostednetwork mode=allow ssid=MyHotspot key=MyPassword123
netsh wlan start hostednetwork
# Mac - 使用内置互联网共享
# 系统偏好设置 → 共享 → 互联网共享
Wireshark配置
打开Wireshark，选择热点对应的网络接口
设置捕获过滤器减少干扰
bash
# 只捕获手机IP的流量
host 192.168.173.100
# 或捕获特定协议
tcp port 80 or tcp port 443 or tcp port 8080方法二：USB网络共享捕获
Android设备设置
bash
# 启用USB调试
adb devices # 验证设备连接
# 设置端口转发
adb forward tcp:5555 tcp:5555
# 使用tcpdump在手机上捕获（需要root）
adb shell
tcpdump -i any -s 0 -w /sdcard/capture.pcap从手机拉取捕获文件
bash
adb pull /sdcard/capture.pcap ./mobile_capture.pcap方法三：路由器端口镜像
支持端口镜像的路由器配置
bash
# 不同路由器命令不同，示例如下：
# 将手机流量镜像到电脑连接的端口
configure terminal
monitor session 1 source interface Wi-Fi0
monitor session 1 destination interface GigabitEthernet0/1Wireshark过滤器和分析技巧
常用显示过滤器
bash
# 按IP地址过滤
ip.addr == 192.168.1.100
!(ip.addr == 192.168.1.100) # 排除特定IP
# 按协议过滤
http or http2 or tls
dns # DNS查询分析
# 按端口过滤
tcp.port == 8080
tcp.port == 443
# 组合过滤器
http and ip.src == 192.168.1.100
tls.handshake.type == 1 # Client Hello
# 应用层过滤
http.request.method == "POST"
http contains "login"
http.response.code == 200特定APP流量识别
bash
# 通过User-Agent识别
http.user_agent contains "MyApp"
# 通过Host识别
http.host contains "api.myapp.com"
# 通过自定义头部识别
http.header contains "X-App-Version"性能测试和分析
网络延迟分析
bash
# 过滤TCP握手过程
tcp.flags.syn == 1 or tcp.flags.ack == 1
# 查看TCP流时序
# 右键 → Follow → TCP Stream带宽使用分析
bash
# 统计流量使用
Statistics → Conversations → IPv4
# 查看流量趋势
Statistics → I/O Graph自定义性能指标
Lua
-- 创建自定义列显示响应时间
-- Edit → Preferences → Appearance → Columns
-- 添加新列，使用字段：tcp.time_deltaAPP启动性能测试
bash
# 捕获过滤器
host 192.168.1.100 and (tcp port 80 or tcp port 443)
# 测试步骤：
1. 清空Wireshark捕获
2. 关闭APP后台进程
3. 开始捕获
4. 启动APP
5. 等待首屏完全加载
6. 停止捕获API请求分析
python
# 分析脚本示例 - 提取API性能数据
import pyshark
import json
def analyze_api_performance(pcap_file):
cap = pyshark.FileCapture(pcap_file, display_filter='http')
api_metrics = []
for packet in cap:
try:
if hasattr(packet, 'http'):
http_layer = packet.http
metric = {
'timestamp': float(packet.sniff_timestamp),
'method': getattr(http_layer, 'request_method', 'N/A'),
'uri': getattr(http_layer, 'request_uri', 'N/A'),
'host': getattr(http_layer, 'host', 'N/A'),
'response_code': getattr(http_layer, 'response_code', 'N/A'),
'length': int(packet.length)
}
api_metrics.append(metric)
except AttributeError:
continue
# 计算性能指标
analyze_metrics(api_metrics)
def analyze_metrics(metrics):
total_requests = len(metrics)
successful_requests = len([m for m in metrics if m['response_code'] == '200'])
print(f"总请求数: {total_requests}")
print(f"成功请求: {successful_requests}")
print(f"成功率: {(successful_requests/total_requests)*100:.2f}%")
# 使用示例
analyze_api_performance('mobile_capture.pcap')安全测试
bash
# 检查明文传输
http and !(http.host contains "localhost")
# 检查弱加密
tls.handshake.type == 2 and
(ssl.handshake.ciphersuites contains "0x0005" or
ssl.handshake.ciphersuites contains "0x0004")
# 检查证书有效性
tls.handshake.certificate使用tshark命令行分析
bash
#!/bin/bash
# automated_mobile_test.sh
# 开始捕获
tshark -i en0 -f "host 192.168.1.100" -w mobile_capture.pcap &
# 执行APP测试场景
echo "开始APP测试..."
# 这里可以集成Appium或其他自动化测试框架
# 等待测试完成
sleep 60
# 停止捕获
pkill -f tshark
# 分析结果
echo "分析网络流量..."
tshark -r mobile_capture.pcap -Y "http" -T fields \
-e frame.time_relative \
-e http.request.method \
-e http.request.uri \
-e http.response.code \
> http_analysis.csv
echo "测试完成，结果保存到 http_analysis.csv"Python自动化分析
python
import subprocess
import time
import pandas as pd
from datetime import datetime
class MobileNetworkAnalyzer:
def __init__(self, device_ip, interface='en0'):
self.device_ip = device_ip
self.interface = interface
self.capture_file = f"capture_{datetime.now().strftime('%Y%m%d_%H%M%S')}.pcap"
def start_capture(self):
"""开始网络捕获"""
cmd = [
'tshark',
'-i', self.interface,
'-f', f'host {self.device_ip}',
'-w', self.capture_file
]
self.capture_process = subprocess.Popen(
cmd,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE
)
print(f"开始捕获流量到 {self.capture_file}")
def stop_capture(self):
"""停止捕获"""
self.capture_process.terminate()
self.capture_process.wait()
print("捕获已停止")
def analyze_performance(self):
"""分析性能指标"""
# HTTP请求分析
http_cmd = [
'tshark', '-r', self.capture_file,
'-Y', 'http',
'-T', 'fields',
'-e', 'frame.time_relative',
'-e', 'http.request.method',
'-e', 'http.request.uri',
'-e', 'http.response.code',
'-e', 'http.content_length'
]
result = subprocess.run(http_cmd, capture_output=True, text=True)
http_data = []
for line in result.stdout.strip().split('\n'):
if line:
parts = line.split('\t')
if len(parts) >= 4:
http_data.append({
'timestamp': float(parts[0]),
'method': parts[1],
'uri': parts[2],
'status_code': parts[3],
'content_length': parts[4] if len(parts) > 4 else '0'
})
return pd.DataFrame(http_data)
def generate_report(self, df):
"""生成性能报告"""
report = {
'total_requests': len(df),
'successful_requests': len(df[df['status_code'] == '200']),
'failed_requests': len(df[df['status_code'] != '200']),
'avg_response_size': df['content_length'].astype(float).mean(),
'test_duration': df['timestamp'].max() if not df.empty else 0
}
print("=== 网络性能测试报告 ===")
print(f"总请求数: {report['total_requests']}")
print(f"成功请求: {report['successful_requests']}")
print(f"失败请求: {report['failed_requests']}")
print(f"成功率: {(report['successful_requests']/report['total_requests'])*100:.2f}%")
print(f"平均响应大小: {report['avg_response_size']:.2f} bytes")
print(f"测试时长: {report['test_duration']:.2f} 秒")
return report
# 使用示例
if __name__ == "__main__":
analyzer = MobileNetworkAnalyzer('192.168.1.100')
try:
analyzer.start_capture()
time.sleep(60) # 运行测试60秒
finally:
analyzer.stop_capture()
df = analyzer.analyze_performance()
report = analyzer.generate_report(df)精彩推荐：点击蓝字即可
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