├── .gitignore ├── README.md ├── conf └── filter.csv ├── csv └── test.csv ├── demo.png ├── etl.py ├── init.py ├── logo.ico ├── main.py ├── requirements.txt ├── server.py └── web ├── index.html └── js ├── echarts.min.js └── jquery-3.4.1.min.js /.gitignore: -------------------------------------------------------------------------------- 1 | /.idea/ 2 | /__pycache__/ 3 | /build/ 4 | /dist/ 5 | /venv/ 6 | /csv/ 7 | /web/sub_title.ini 8 | /web/tmp.json 9 | *.spec -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # SOC_Sankey_Generator 2 | 3 | ## 简介 4 | 这是一款从SOC日志中进行数据ETL与数据可视化的工具,可以快速将日志呈现为Sankey图,适合安全日报、周报、月报中使用;也适合HW行动中防守方每日汇报。 5 | 6 | ## 环境&依赖 7 | python3 8 | pandas(必选,用于处理csv) 9 | pyinstaller(可选,exe打包用) 10 | 11 | ## 用法 12 | 将日志文件整理成表头为:**源地址,目的地址,事件名称,事件数** 的CSV格式文件,放于csv目录下 13 | 运行mian.py或者main.exe按提示输入完成数据处理,最后浏览器访问 http://127.0.0.1:8900 即可。 14 | 15 | ## 展示 16 | ![alt demo](demo.png "demo") 17 | 18 | ## 过滤器用法 19 | 本工具支持包含与排除两种正则过滤器,请在conf目录下的filter.csv文件中进行配置。 20 | 配置说明为: 21 | 22 | >第一列:过滤模式[in=包含,ex=排除] 23 | >第二列:字段列号[0=源地址,1=目的地址,2=攻击方式] 24 | >第三列:匹配值[正则匹配] 25 | >第四列:备注 26 | 27 | 28 | 例如: 29 | ```ex,0,114.114.114.114,备注``` 30 | 为:排除源地址是114.114.1114.114的事件 31 | 32 | ```in,2,暴力破解,备注 ``` 33 | 为:仅查看事件名称中包含暴力破解的事件 34 | 35 | 当过滤器文件内容发生改动时,工具会自动对数据进行重新整理,可直接刷新网页页面。 36 | 37 | ## 打包命令 38 | ```pyinstaller -i logo.ico -F main.py ``` -------------------------------------------------------------------------------- /conf/filter.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LennyLeng/SOC_Sankey_Generator/9c26829c4697f20da9c9a06b1f20da87a06d27f4/conf/filter.csv -------------------------------------------------------------------------------- /csv/test.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LennyLeng/SOC_Sankey_Generator/9c26829c4697f20da9c9a06b1f20da87a06d27f4/csv/test.csv -------------------------------------------------------------------------------- /demo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LennyLeng/SOC_Sankey_Generator/9c26829c4697f20da9c9a06b1f20da87a06d27f4/demo.png -------------------------------------------------------------------------------- /etl.py: -------------------------------------------------------------------------------- 1 | #coding=utf8 2 | 3 | import pandas as pd 4 | import json 5 | import re 6 | 7 | def get_filter(csv_file): 8 | filter_list = [] 9 | data = pd.read_csv(csv_file, encoding='gbk', header=0) 10 | 11 | for data_row in data.values: 12 | if (data_row[0].startswith('#')): 13 | continue 14 | dict = {} 15 | dict['filter_type'] = data_row[0] 16 | dict['col_index'] = int(data_row[1]) 17 | dict['pattern_val'] = data_row[2] 18 | dict['tip'] = data_row[3] 19 | filter_list.append(dict) 20 | return filter_list 21 | 22 | 23 | def generate_json(csv_file, limit, filter_list): 24 | print('开始抽取整理数据...') 25 | # 读取csv文件,thousands用于处理千分位分割符,header用于指定第一行为表头 26 | data = pd.read_csv(csv_file, encoding='gbk', header=0, thousands=',') 27 | #按照事件数量降序排列 28 | data = data.sort_values(by='事件数',ascending=False) 29 | 30 | # 生成打环判定源地址集合,集合set具有不重复特征 31 | i0_set_tmp = set() 32 | i1_set_tmp = set() 33 | 34 | links_tmp = {} 35 | nodes_tmp = set() 36 | links = [] 37 | nodes = [] 38 | 39 | # 生成links,nodes_tmp 40 | 41 | i = 0 42 | for data_row in data.values: 43 | # data_row[0] => 源地址 44 | # data_row[1] => 目的地址 45 | # data_row[2].replace(" ", "") => 事件名称 46 | # data_row[3] => 事件数 47 | if (limit == '' or i < int(limit)): 48 | 49 | #删除首尾空白不可见符 50 | data_row[0] = (str)(data_row[0]) 51 | data_row[0] = data_row[0].strip() 52 | 53 | data_row[1] = (str)(data_row[1]) 54 | data_row[1] = data_row[1].strip() 55 | 56 | data_row[2] = (str)(data_row[2]) 57 | data_row[2] = data_row[2].strip() 58 | 59 | #处理事件名称中的字符空格 60 | data_row[2] = data_row[2].replace(" ", "") 61 | 62 | #filter list policy 开始 63 | is_exclude = False 64 | for filter in filter_list: 65 | try: 66 | if(filter['filter_type'] == 'ex' and re.search(filter['pattern_val'], data_row[filter['col_index']])): 67 | print(data_row[0], '\t=>\t', data_row[2][:10] + '…', '\t=>\t', data_row[1], '\t|\t',str(data_row[3]), 68 | '\t',filter['tip'],'\t忽略') 69 | is_exclude = True 70 | break 71 | 72 | if (filter['filter_type'] == 'in' and not re.search(filter['pattern_val'],data_row[filter['col_index']])): 73 | print(data_row[0], '\t=>\t', data_row[2][:10] + '…', '\t=>\t', data_row[1], '\t|\t', 74 | str(data_row[3]), 75 | '\t', '未'+filter['tip'], '\t忽略') 76 | is_exclude = True 77 | break 78 | 79 | except: 80 | pass 81 | 82 | if(is_exclude): 83 | continue 84 | # filter list policy 结束 85 | 86 | if (data_row[2] == '' or data_row[2] == '空值'): 87 | print(data_row[0], '\t=>\t', data_row[2][:10] + '…', '\t=>\t', data_row[1], '\t|\t', str(data_row[3]), 88 | '\t事件名称为空\t修正') 89 | data_row[2] = '空名称' 90 | 91 | if (data_row[0] == data_row[1] or data_row[1] == '空值'): 92 | print(data_row[0], '\t=>\t', data_row[2][:10] + '…', '\t=>\t', data_row[1], '\t|\t', str(data_row[3]), 93 | '\t源目相同或者目的为空\t修正') 94 | data_row[1] = '0.0.0.0' 95 | i1_set_tmp.add(data_row[1]) 96 | 97 | if (data_row[0] == '空值'): 98 | print(data_row[0], '\t=>\t', data_row[2][:10] + '…', '\t=>\t', data_row[1], '\t|\t', str(data_row[3]), 99 | '\t源为空\t修正') 100 | data_row[0] = '0.0.0.0' 101 | i0_set_tmp.add(data_row[0]) 102 | 103 | if (data_row[1] in i0_set_tmp ): 104 | print(data_row[0], '\t=>\t', data_row[2][:10] + '…', '\t=>\t', data_row[1], '\t|\t', str(data_row[3]), 105 | '\t出现打环情况\t忽略') 106 | continue 107 | 108 | if (data_row[0] in i1_set_tmp ): 109 | print(data_row[0], '\t=>\t', data_row[2][:10] + '…', '\t=>\t', data_row[1], '\t|\t', str(data_row[3]), 110 | '\t出现多级情况\t忽略') 111 | continue 112 | 113 | i0_set_tmp.add(data_row[0]) 114 | i1_set_tmp.add(data_row[1]) 115 | 116 | nodes_tmp.add(data_row[0]) 117 | nodes_tmp.add(data_row[1]) 118 | nodes_tmp.add(data_row[2]) 119 | 120 | tmp = list() 121 | tmp.append(data_row[0]) 122 | tmp.append(data_row[2]) 123 | tmp = json.dumps(tmp) 124 | if (tmp in links_tmp): 125 | links_tmp[tmp] += data_row[3] 126 | else: 127 | links_tmp[tmp] = data_row[3] 128 | 129 | tmp = list() 130 | tmp.append(data_row[2]) 131 | tmp.append(data_row[1]) 132 | tmp = json.dumps(tmp) 133 | if (tmp in links_tmp): 134 | links_tmp[tmp] += data_row[3] 135 | else: 136 | links_tmp[tmp] = data_row[3] 137 | 138 | else: 139 | #print(data_row[0], data_row[1],data_row[2],data_row[3], '!!!') 140 | break 141 | i += 1 142 | 143 | 144 | # 生成nodes 145 | for data_row in nodes_tmp: 146 | dic = {} 147 | dic['name'] = data_row 148 | nodes.append(dic) 149 | 150 | for data_row in links_tmp: 151 | tmp = json.loads(data_row) 152 | dic = {} 153 | dic['source'] = tmp[0] 154 | dic['target'] = tmp[1] 155 | dic['value'] = links_tmp[data_row] 156 | links.append(dic) 157 | 158 | data = {'nodes': nodes, 'links': links} 159 | print('抽取整理数据完成!') 160 | return json.dumps(data) 161 | 162 | if __name__ == '__main__': 163 | filter_list = get_filter('conf/filter.csv') 164 | json_data = generate_json('csv/test.csv', '', filter_list) 165 | with open('web/tmp.json', 'w') as f: 166 | f.write(json_data) -------------------------------------------------------------------------------- /init.py: -------------------------------------------------------------------------------- 1 | #coding=utf8 2 | import etl 3 | import os 4 | 5 | def init(): 6 | print("启明星辰SOC日志Sankey图分析生成工具V1.5.2") 7 | # 1.0 基本功能 8 | # 1.1 修复snakeyjson数据原到目的的数值不一致问题 9 | # 1.2 增加白名单排除配置文件 10 | # 1.3 修复filter正则匹配问题,使用更宽松的search代替match 11 | # 1.31 修复源ip未空情况 12 | # 1.4 修复i0源地址集排除逻辑,打环判定更精确;修复http.server存在缓存,刷新数据不是最新的情况;修复filter文件不在时程序报错的情况。 13 | # 1.5 重构i0源地址集排除逻辑,优化padas读取csv文件逻辑,使用thousands用于处理千分位分割符,使用header用于指定第一行为表头 14 | # 1.5.1 新增多级排除逻辑,优化padas读取config文件逻辑 15 | # 1.5.2 bugfix 极端情况字段存在float情况,强制转换至str 16 | 17 | print("作者:Lenny\n") 18 | 19 | # 选择文件 20 | print('将启明SOC日志文件整理成表头为:[源地址,目的地址,事件名称,事件数]的CSV格式文件,放于csv目录下') 21 | csv_files = dict() 22 | data_row = 1 23 | for file in os.listdir('csv'): 24 | if (file[-4:] == '.csv'): 25 | print("[%d] %s" % (data_row, file)) 26 | csv_files[str(data_row)] = file 27 | data_row += 1 28 | select_index = input('输入要加载的文件序号[1-%d]:' % (data_row - 1)) 29 | print("已选择:%s" % (csv_files[str(select_index)])) 30 | # 输入日期 31 | date = input('输入图表副标题:') 32 | with open('web/sub_title.ini', 'w', encoding='utf-8') as f: 33 | f.write(date) 34 | 35 | # 输入提取条数 36 | limit = input('输入提取条数(不输入默认为全部提取,建议50条):') 37 | 38 | return (csv_files[str(select_index)], limit) -------------------------------------------------------------------------------- /logo.ico: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LennyLeng/SOC_Sankey_Generator/9c26829c4697f20da9c9a06b1f20da87a06d27f4/logo.ico -------------------------------------------------------------------------------- /main.py: -------------------------------------------------------------------------------- 1 | #coding=utf8 2 | 3 | import etl 4 | import server 5 | import init 6 | import os 7 | import time 8 | import multiprocessing 9 | import traceback 10 | 11 | def generate_json_and_write_file(csv_file, limit): 12 | filter_chang_time = float(0) 13 | while True: 14 | try: 15 | if(filter_chang_time < os.stat('conf/filter.csv').st_mtime): 16 | filter_list = etl.get_filter('conf/filter.csv') 17 | json_data = etl.generate_json('csv/' + csv_file, limit, filter_list) 18 | with open('web/tmp.json', 'w') as f: 19 | f.write(json_data) 20 | print("web服务已启动,打开浏览器访问http://127.0.0.1:%d" % (server.PORT)) 21 | filter_chang_time = os.stat('conf/filter.csv').st_mtime 22 | except: 23 | #当filter文件不存在时,重置文件改变时间 24 | traceback.print_exc() 25 | filter_chang_time = float(0) 26 | time.sleep(1) 27 | 28 | def run(): 29 | (csv_file, limit) = init.init() 30 | json_p = multiprocessing.Process(target=generate_json_and_write_file, args=(csv_file, limit)) 31 | json_p.start() 32 | http_p = multiprocessing.Process(target=server.run) 33 | http_p.start() 34 | 35 | def debug(): 36 | (csv_file, limit) = init.init() 37 | http_p = multiprocessing.Process(target=server.run) 38 | http_p.start() 39 | generate_json_and_write_file(csv_file, limit) 40 | 41 | if __name__ == '__main__': 42 | multiprocessing.freeze_support() 43 | run() -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | pandas 2 | pyinstaller -------------------------------------------------------------------------------- /server.py: -------------------------------------------------------------------------------- 1 | import http.server 2 | PORT = 8900 3 | DIRECTORY = "web" 4 | def run(): 5 | class Handler(http.server.SimpleHTTPRequestHandler): 6 | def __init__(self, *args, **kwargs): 7 | super().__init__(*args, directory=DIRECTORY, **kwargs) 8 | 9 | def end_headers(self): 10 | self.send_cacheless_headers() 11 | http.server.SimpleHTTPRequestHandler.end_headers(self) 12 | 13 | def send_cacheless_headers(self): 14 | self.send_header("Cache-Control", "no-cache, no-store, must-revalidate") 15 | self.send_header("Pragma", "no-cache") 16 | self.send_header("Expires", "0") 17 | 18 | try: 19 | httpd = http.server.HTTPServer(("", PORT), Handler) 20 | httpd.serve_forever() 21 | except KeyboardInterrupt: 22 | print('接收到关闭指令,退出程序') 23 | httpd.shutdown() 24 | 25 | if __name__ == '__main__': 26 | run() -------------------------------------------------------------------------------- /web/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
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