Python SQL注入检测插件 Python实现SQL注入检测插件实例代码

时间:2021-03-30 wmathor 人气:0

扫描器需要实现的功能思维导图

爬虫编写思路

首先需要开发一个爬虫用于收集网站的链接，爬虫需要记录已经爬取的链接和待爬取的链接，并且去重，用 Python 的set()就可以解决，大概流程是：

输入 URL
下载解析出 URL
URL 去重，判断是否为本站
加入到待爬列表
重复循环

SQL 判断思路

通过在 URL 后面加上AND %d=%d或者OR NOT (%d>%d)
%d后面的数字是随机可变的
然后搜索网页中特殊关键词，比如：

MySQL 中是 SQL syntax.*MySQL
Microsoft SQL Server 是 Warning.*mssql_
Microsoft Access 是 Microsoft Access Driver
Oracle 是 Oracle error
IBM DB2 是 DB2 SQL error
SQLite 是 SQLite.Exception
...

通过这些关键词就可以判断出所用的数据库

还需要判断一下 waf 之类的东西，有这种东西就直接停止。简单的方法就是用特定的 URL 访问，如果出现了像IP banned，fierwall之类的关键词，可以判断出是waf。具体的正则表达式是(?i)(\A|\b)IP\b.*\b(banned|blocked|bl(a|o)ck\s?list|firewall)
开发准备展开目录

请安装这些库

pip install requests
pip install beautifulsoup4

实验环境是 Linux，创建一个Code目录，在其中创建一个work文件夹，将其作为工作目录

目录结构

/w8ay.py // 项目启动主文件
/lib/core // 核心文件存放目录
/lib/core/config.py // 配置文件
/script // 插件存放
/exp // exp和poc存放

步骤

SQL 检测脚本编写

DBMS_ERRORS = {
  'MySQL': (r"SQL syntax.*MySQL", r"Warning.*mysql_.*", r"valid MySQL result", r"MySqlClient\."),
  "PostgreSQL": (r"PostgreSQL.*ERROR", r"Warning.*\Wpg_.*", r"valid PostgreSQL result", r"Npgsql\."),
  "Microsoft SQL Server": (r"Driver.* SQL[\-\_\ ]*Server", r"OLE DB.* SQL Server", r"(\W|\A)SQL Server.*Driver", r"Warning.*mssql_.*", r"(\W|\A)SQL Server.*[0-9a-fA-F]{8}", r"(?s)Exception.*\WSystem\.Data\.SqlClient\.", r"(?s)Exception.*\WRoadhouse\.Cms\."),
  "Microsoft Access": (r"Microsoft Access Driver", r"JET Database Engine", r"Access Database Engine"),
  "Oracle": (r"\bORA-[0-9][0-9][0-9][0-9]", r"Oracle error", r"Oracle.*Driver", r"Warning.*\Woci_.*", r"Warning.*\Wora_.*"),
  "IBM DB2": (r"CLI Driver.*DB2", r"DB2 SQL error", r"\bdb2_\w+\("),
  "SQLite": (r"SQLite/JDBCDriver", r"SQLite.Exception", r"System.Data.SQLite.SQLiteException", r"Warning.*sqlite_.*", r"Warning.*SQLite3::", r"\[SQLITE_ERROR\]"),
  "Sybase": (r"(?i)Warning.*sybase.*", r"Sybase message", r"Sybase.*Server message.*"),
}

通过正则表达式就可以判断出是哪个数据库了

for (dbms, regex) in ((dbms, regex) for dbms in DBMS_ERRORS for regex in DBMS_ERRORS[dbms]):
  if (re.search(regex,_content)):
    return True

下面是我们测试语句的payload

BOOLEAN_TESTS = (" AND %d=%d", " OR NOT (%d=%d)")

用报错语句返回正确的内容和错误的内容进行对比

for test_payload in BOOLEAN_TESTS:
  # Right Page
  RANDINT = random.randint(1, 255)
  _url = url + test_payload % (RANDINT, RANDINT)
  content["true"] = Downloader.get(_url)
  _url = url + test_payload % (RANDINT, RANDINT + 1)
  content["false"] = Downloader.get(_url)
  if content["origin"] == content["true"] != content["false"]:
    return "sql found: %" % url

这句

content["origin"] == content["true"] != content["false"]

意思就是当原始网页等于正确的网页不等于错误的网页内容时，就可以判定这个地址存在注入漏洞

完整代码：

import re, random
from lib.core import Download
def sqlcheck(url):
  if (not url.find("?")): # Pseudo-static page
    return false;
  Downloader = Download.Downloader()
  BOOLEAN_TESTS = (" AND %d=%d", " OR NOT (%d=%d)")
  DBMS_ERRORS = {
    # regular expressions used for DBMS recognition based on error message response
    "MySQL": (r"SQL syntax.*MySQL", r"Warning.*mysql_.*", r"valid MySQL result", r"MySqlClient\."),
    "PostgreSQL": (r"PostgreSQL.*ERROR", r"Warning.*\Wpg_.*", r"valid PostgreSQL result", r"Npgsql\."),
    "Microsoft SQL Server": (r"Driver.* SQL[\-\_\ ]*Server", r"OLE DB.* SQL Server", r"(\W|\A)SQL Server.*Driver", r"Warning.*mssql_.*", r"(\W|\A)SQL Server.*[0-9a-fA-F]{8}", r"(?s)Exception.*\WSystem\.Data\.SqlClient\.", r"(?s)Exception.*\WRoadhouse\.Cms\."),
    "Microsoft Access": (r"Microsoft Access Driver", r"JET Database Engine", r"Access Database Engine"),
    "Oracle": (r"\bORA-[0-9][0-9][0-9][0-9]", r"Oracle error", r"Oracle.*Driver", r"Warning.*\Woci_.*", r"Warning.*\Wora_.*"),
    "IBM DB2": (r"CLI Driver.*DB2", r"DB2 SQL error", r"\bdb2_\w+\("),
    "SQLite": (r"SQLite/JDBCDriver", r"SQLite.Exception", r"System.Data.SQLite.SQLiteException", r"Warning.*sqlite_.*", r"Warning.*SQLite3::", r"\[SQLITE_ERROR\]"),
    "Sybase": (r"(?i)Warning.*sybase.*", r"Sybase message", r"Sybase.*Server message.*"),
  }
  _url = url + "%29%28%22%27"
  _content = Downloader.get(_url)
  for (dbms, regex) in ((dbms, regex) for dbms in DBMS_ERRORS for regex in DBMS_ERRORS[dbms]):
    if (re.search(regex,_content)):
      return True
  content = {}
  content['origin'] = Downloader.get(_url)
  for test_payload in BOOLEAN_TESTS:
    # Right Page
    RANDINT = random.randint(1, 255)
    _url = url + test_payload % (RANDINT, RANDINT)
    content["true"] = Downloader.get(_url)
    _url = url + test_payload % (RANDINT, RANDINT + 1)
    content["false"] = Downloader.get(_url)
    if content["origin"] == content["true"] != content["false"]:
      return "sql found: %" % url

将这个文件命名为sqlcheck.py，放在/script目录中。代码的第 4 行作用是查找 URL 是否包含?，如果不包含，比方说伪静态页面，可能不太好注入，因此需要过滤掉

爬虫的编写

爬虫的思路上面讲过了，先完成 URL 的管理，我们单独将它作为一个类，文件保存在/lib/core/UrlManager.py

#-*- coding:utf-8 -*-

class UrlManager(object):
  def __init__(self):
    self.new_urls = set()
    self.old_urls = set()
    
  def add_new_url(self, url):
    if url is None:
      return
    if url not in self.new_urls and url not in self.old_urls:
      self.new_urls.add(url)
   
  def add_new_urls(self, urls):
    if urls is None or len(urls) == 0:
      return
    for url in urls:
      self.add_new_url(url)
    
  def has_new_url(self):
    return len(self.new_urls) != 0
   
  def get_new_url(self):
    new_url = self.new_urls.pop()
    self.old_urls.add(new_url)
    return new_url

为了方便，我们也将下载功能单独作为一个类使用，文件保存在lib/core/Downloader.py

#-*- coding:utf-8 -*-
import requests

class Downloader(object):
  def get(self, url):
    r = requests.get(url, timeout = 10)
    if r.status_code != 200:
      return None
    _str = r.text
    return _str
  
  def post(self, url, data):
    r = requests.post(url, data)
    _str = r.text
    return _str
  
  def download(self, url, htmls):
    if url is None:
      return None
    _str = {}
    _str["url"] = url
    try:
      r = requests.get(url, timeout = 10)
      if r.status_code != 200:
        return None
      _str["html"] = r.text
    except Exception as e:
      return None
    htmls.append(_str)

特别说明，因为我们要写的爬虫是多线程的，所以类中有个download方法是专门为多线程下载专用的

在lib/core/Spider.py中编写爬虫

#-*- coding:utf-8 -*-

from lib.core import Downloader, UrlManager
import threading
from urllib import parse
from urllib.parse import urljoin
from bs4 import BeautifulSoup

class SpiderMain(object):
  def __init__(self, root, threadNum):
    self.urls = UrlManager.UrlManager()
    self.download = Downloader.Downloader()
    self.root = root
    self.threadNum = threadNum
  
  def _judge(self, domain, url):
    if (url.find(domain) != -1):
      return True
    return False
  
  def _parse(self, page_url, content):
    if content is None:
      return
    soup = BeautifulSoup(content, 'html.parser')
    _news = self._get_new_urls(page_url, soup)
    return _news
    
  def _get_new_urls(self, page_url, soup):
    new_urls = set()
    links = soup.find_all('a')
    for link in links:
      new_url = link.get('href')
      new_full_url = urljoin(page_url, new_url)
      if (self._judge(self.root, new_full_url)):
        new_urls.add(new_full_url)
    return new_urls
    
  def craw(self):
    self.urls.add_new_url(self.root)
    while self.urls.has_new_url():
      _content = []
      th = []
      for i in list(range(self.threadNum)):
        if self.urls.has_new_url() is False:
          break
        new_url = self.urls.get_new_url()
        
        ## sql check
        try:
          if (sqlcheck.sqlcheck(new_url)):
            print("url:%s sqlcheck is valueable" % new_url)
        except:
          pass
            
        print("craw:" + new_url)
        t = threading.Thread(target = self.download.download, args = (new_url, _content))
        t.start()
        th.append(t)
      for t in th:
        t.join()
      for _str in _content:
        if _str is None:
          continue
        new_urls = self._parse(new_url, _str["html"])
        self.urls.add_new_urls(new_urls)

爬虫通过调用craw()方法传入一个网址进行爬行，然后采用多线程的方法下载待爬行的网站，下载之后的源码用_parse方法调用BeautifulSoup进行解析，之后将解析出的 URL 列表丢入 URL 管理器，这样循环，最后只要爬完了网页，爬虫就会停止

threading库可以自定义需要开启的线程数，线程开启后，每个线程会得到一个 url 进行下载，然后线程会阻塞，阻塞完毕后线程放行

爬虫和 SQL 检查的结合

在lib/core/Spider.py文件引用一下from script import sqlcheck，在craw()方法中，取出新的 URL 地方调用一下

##sql check
try:
  if(sqlcheck.sqlcheck(new_url)):
    print("url:%s sqlcheck is valueable"%new_url)
except:
  pass

用try检测可能出现的异常，绕过它，在文件w8ay.py中进行测试

#-*- coding:utf-8 -*-
'''
Name: w8ayScan
Author: mathor
Copyright (c) 2019
'''
import sys
from lib.core.Spider import SpiderMain
def main():
  root = "https://wmathor.com"
  threadNum = 50
  w8 = SpiderMain(root, threadNum)
  w8.craw()
 
if __name__ == "__main__":
  main()

很重要的一点！为了使得lib和script文件夹中的.py文件可以可以被认作是模块，请在lib、lib/core和script文件夹中创建__init__.py文件，文件中什么都不需要写

总结

SQL 注入检测通过一些payload使页面出错，判断原始网页，正确网页，错误网页即可检测出是否存在 SQL 注入漏洞
通过匹配出 sql 报错出来的信息，可以正则判断所用的数据库

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