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First cURL command will remove the unwanted text. The next request is a "failed" log in user:pass , the last is successful admin:password. TL;DR : Blacklisting, you are ignoring all results that do not contain phrase.

Whitelisting, you are looking for a specific value to be successful. We need to identify a key point to "mark" how the web application will respond when a login is incorrect aka blackisting or if it was successful aka whitelisting. Blacklisting often contains more false positives , where it believes it has successfully logged in, when it really failed. This is because you have to rule out "every" possible combination other than a successful login. Depending on the web application, it may respond differently for any number of reasons at any stage.

If the marker does not appear on the page, it will believe it logged in correctly. If the web application responded with incorrect CSRF token , the program would believe it was a successful login, even though it was not. Using incorrect would be better here as it appears in both statements. However, if the marker is too general, this may cause issues.

The marker needs to be as unique as possible. The advantage of using blacklisting is that it is easier to discover a failed login attempt rather than a successful one, so it is easier to begin with. Another benefit is, you get to see how the web application responds differently over time and all responses.

This means it is easier to debug issues more quickly. For whitelisting , they give a more accurate way of knowing if you have logged in correctly, rather than having to rule out every response which is incorrect. The down side to it is if, during the request the page starts to respond differently, we might not be aware, and will just blindly keep attacking, which might be a waste of time.

An example is, if an API key has reached its maximum amount of requests for a given period of time. The "best" way would be to use a mixture of them; ignore all pages that respond in a certain way, print pages which do not match any known response, and quit if a certain value is found Hydra does not support this, but Patator supports various operators and condition requirements. Getting back to DVWA brute forcing, we could risk doing a whitelist attack and make an educated guess at the response such as: welcome , logged in , successful , hello , thank you etc.

As the HTML is more of a unique marker, we will start by using that sometimes web applications put various statics in the response, such as page generation time, or a full data stamp which may cause the page length to be different each request - comparing multiple reponses could rule this out.

This means any pages which do contain it as incorrect. Therefore any pages which do not contain the phrase, will be seen as "successful" hopefully this is correct and the web app does not start to behave differently. If it does, we will need ether to also include the additional value or to re-think the marker completely. Normally, people are after the "main" user account on the system often called admin , root , system , as this is the account that normally has most access over the system.

Often this has user id "1" as it is the "first" user account on the system. Depending on the web application there might be "group" control, allowing multiple users to share certain values. If this is the case, there is often an "administrative" group control which is desirable to attackers, which will be a good alterative if the main account is inaccessible.

So during our attacks, we will do two commands. One for a "single user", where we try for the main account in DVWA case, admin , and then another command to attack multiple users. DVWA by default comes with a total of five accounts. We want to target them all! We have crafted a username wordlist ourselves. How do we know what values? Depends on the web application! There are various ways to enumerate users on the system Are they made public at all?

Are we able to exact anything from "Forgotten user password"? Can we map "User IDs" to usernames? Email addresses? Can we just "guest"? However, in this case, for DVWA:. A wordlist sometimes referred to as a dictionary file is just a plain text file, which contains possible values to try separated out by a common perimeter often a new line. The file extension does not matter for the text file often they are. We are going to cycle through the usernames before trying the next password, allowing us to focus on the password.

This is an in-built feature in Hydra -u , and Patator supports this based on the ID value of the wordlist. It will not matter if there is a single user in the attack, only when trying multiple usernames. The reason why this could speed up an attack is, un fortunately people still use common passwords. Different users may have the same password as they do not have to be unique whereas usernames do.

There is not often a need to alter it from default values unless trying to debug. Brute forcing is slow. The speed will be because of the slowest point in the system, and there are various places where it will slow down. Thereforce using custom built wordlists should give a higher success rate than using a general one e. Due to the amount of time it may possibly take, there is an urge to tweak the brute force method e. However, there is not a fixed "magic number" it is more of an "art", than a "science".

Altering these values too much, may cause more issues in the long run. Example: putting the thread count "too high", could cause an extreme amount of requests to a web server. Another thing could be, for each request the OS sets aside a certain amount of system resources and soon the target system may run out of memory. It all depends on the setup, the target, and, its configuration. If everything is working "correctly" lowering the wait time does not often archive anything.

Example: if the timeout is set to 10 seconds, but it takes less than 1 second to respond, having it at 5 seconds or even 3 seconds will not make any difference. On one hand, having the value too low could mean valid requests are ignored. Another thing to keep in mind, depending on the tool used, it may not display if a request "timed out" or even check periodically to see if the service is still active.

Meaning the part of the attack could be pointless. The last point is, the system may respond differently depending "how it pushed" and "how much it was pushed". Instead, what might be a better methodology, is having the wordlist sorted in a certain order. This may help speed up the attack having the more common values at the start.

There are various ways to create a custom targeted wordlist, but this going offtopic. It might also mean taking multiple runs for it to be successful, one at once serial rather than parallel. So each time the size of the wordlist would grow, taking longer, but there will be less chance of missing the "low hanging fruit".

I believe it is "better" to make lots of smaller attacks rather than being lazy and making one big one. Because the response times were so low, the slowest point normally was not the network connection therefore increasing the threads would not help a great deal in this case. See the benchmark results! This is probably the "most well-known" tool as it has been around since August with the public release of v0.

Here are snippets from the documentation readme. We could use wireshark or tcpdump to monitor what is sent to and from Hydra, as well as use the in-built "debug" flag -d. However, the issue with all of these is there is an awful lot of data put on the screen, which makes it harder to understand what is going on.

Incomes the use of a "proxy". Rather than it being used in an attempt to "hide your IP" by using another machine fisrt in order to connect to the target, instead of going directt , we can use it to inspect the traffic.

Using Burp Proxy Suite , we can monitor what is being sent to and from our target. This way we can check to see if Hydra is acting in our desired way and reacts correctly when there is a successful login. By using Burp, we are able to quickly filter, sort and compare all of the requests. It is also worth noting that Hydra does come with a verbose option -v to display more information than standard, but not as much as debug! Becuase we are debugging, the thread count is set to 1, using a larger timeout value as well as to wait after each thread finishes.

Note, if we are going to use Burp, make sure "Invisible Proxy Mode" is enabled see below! The top code snippet, will brute force a single user , the admin user and then stop the attack when the user is found -F. It will also show all combination attempts -V as well as blacklisting a certain phrase a successful login will NOT contain this value. The bottom one will brute force all five users which are thereby default in DVWA , but will take much longer as there are many more combinations to try.

It will also not display combination attempts missing -V. Rather than looking for a page that does not include a certain value, this time look for a certain phrase once we are logged in whitelisting. More about blacklisting vs whitelisting at the end. Patator is not as well-known as either Hydra, Medusa, Ncrack, Metasploit, or Nmap probably due to the it being the "youngest" tool In November v0.

Patator is incredibly powerful. It is written in python, rather than C which makes Patator use more system resources , however, it makes up for this as it has an it has an awful lot more features and options. It is not straightforward to use, and there is limited documentation for it. I also found checking the actual source code to be helpful as it gave me a better understanding.

It is written in Python, which makes it easier to understand. Patator is more verbose in its output compared to Hydra, as out of the box Patator will display all attempts made you need to tell it to ignore requests based on a parameter. Plus, it will have various columns displaying results which thread made the request, size of response, code response etc.

This helps to build up a bigger picture overall of what is going on with the attack. Patator has more of a "fuzzer" feel to it, rather than being a brute force tool. Unless you tell it not to, Patator will not only do it but display the result of it and keep on doing it until instructed otherwise. For whatever reason, if the displayed output is not enough, then Patator can be put through a proxy to monitor its actions Burp does not need to be in "Invisible Proxy Mode".

Forex Hydra Strategy is easy to install and run on your MT4 but it is also just as easily removed, if required. Although our trend indicator is quite a comprehensive tool it is still very lightweight because it was programmed from the ground up to be extremely fast and responsive. Not only will it run on multiple charts but it can also run with different settings on each chart. The end result is that you can easily run Forex Hydra Strategy on multiple charts without slowing down the performance of your MetaTrader.

The beauty of the Forex Hydra Strategy is that it is simple to use but also very versatile. Many novice traders over-complicate their trading charts, sometimes viewing more than 5 indicators at once. In these type of a set ups some indicators will send conflicting signals and the user may feel mentally exhausted after each trading session.

Forex Hydra Strategy will generate trading signals based on predefined settings. In addition to big arrows drawn on the charts the signals can be delivered as a small pop up window with a sound alert as seen in image , email message, or a push notification sent to your mobile device such as phone or tablet. Once the trend indicator is installed and running you will be able to receive free trading alerts continuously without any monthly fees.

You will no longer need to stay glued to your monitor screen for hours waiting for a favorable setup. In addition to arrows on the chart and pop ups in MetaTrader our custom MT4 trend indicator will also send email alerts and push notifications to your mobile. The email alerts, as well as other notifications can be switched ON or OFF in the indicator settings.

The trading signals can also be delivered to your mobile via a push notification. In order for this to work you will need to install the Meta Trader 4 App on your mobile. Push notifications are sent almost instantaneously and because of that they are much faster than email. In order to receive the trading signals to your email address or your phone, your MetaTrader 4 needs to be configured with your server details, email account, phone number, and it needs to be running.

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