然后使用我B哥的webalivescan扫描

https://github.com/broken5/WebAliveScan

写了个自己字典生成规则：脚本

infolist = []
dictionaryFile = open('C:/Users/challenger/Desktop/工具/test.txt', 'w')
try:
    # 读取个人信息文件，并按行存入lines
    informationFile = open('C:/Users/challenger/Desktop/工具/whatweb_set.txt', 'r', encoding='utf-8')
    lines = informationFile.readlines()  # 依次读取每行
    #lines=dictionaryFile.readlines()
    for line in lines:
        line = line.strip('\\n\\r')
        if   "bak"  in line:
            infolist.append("{'path': '" + line + "', 'status': 200, 'type': 'application/octet-stream'},")
        else:
            infolist.append("{'path': '" + line + "', 'status': 200, 'type': 'html'},")
        #infolist.extend("{'path': '"+line+"', 'status': 200, 'type': 'html'},")
    print(infolist)
except Exception as e:
    print(e + "\\n")
    print("Read person_information error!")
for a in range(len(infolist)):
    dictionaryFile.write(infolist[a] + '\\n')

2.寻找靶标系统源码

然后又是相同套路从fofa寻找相同系统，有一百多个站基本备份就是稳得webalivescan再扫一波备份,扫到一个bin.rar

webalivescan再扫一波备份,扫到一个bin.rar

代码审计