What is the CSRF or Cross-Site Request Forgery attack?

The Cross-Site Request Forgery attack or CSRF attack is an attack in which an attacker can exploit the authentication cookies of a victim and send a malicious request to a web application using the authentication cookies. Let’s try to understand how the attack works in more detail.

How does the CSRF attack work?

Most websites use cookies to store user credentials associated with the site. When a user authenticates himself to the web application, the cookie is set. Later, the information in the cookie is included along with every HTTP request sent by the authenticated user.

Suppose a user has authenticated in a banking site, bank.com, and the corresponding cookie is set in his machine. So, at this point, whatever request his browser will send to the banking site, the cookie will be used.

Now, an attacker, XYZ, wants to exploit the cookie and trick the user into transferring $10,000 to the attacker’s account. And the corresponding HTTP request for that operation is:

http://bank.com/transfer.do?acct=XYZ&amount=10000

So, the attacker sends an email to the user and tricks him into clicking on a link. Let’s say the link contains the following:

<a href=”http://bank.com/transfer.do?acct=XYZ&amount=10000”>Interesting Pictures! </a>

When the user clicks on the link while he is already authenticated to the banking site, the action will be performed, and $10,000 will be transferred to the attacker XYZ.

Here, I just gave one simple example to understand the attack. In a similar way, the user may be tricked into changing his password or email address. The user may even be tricked into purchasing something. HTTP GET and HTTP POST requests are equally vulnerable to this attack.

How to prevent CSRF attacks?

The most common method of preventing CSRF attacks is to append some secret and unpredictable challenge token to each request submitted by the user. Such tokens must be unique per session and also unique per request. As a result, even if the victim is tricked into clicking on some malicious link and submits a …

Facebooktwitterredditpinterestlinkedinmail

Calculate the pseudoinverse of a matrix using Python

What is the pseudoinverse of a matrix? We know that if A is a square matrix with full rank, then A-1 is said to be the inverse of A if the following condition holds: $latex AA^{-1}=A^{-1}A=I $ The pseudoinverse or the Moore-Penrose inverse of a matrix is a...

Cholesky decomposition using Python

What is Cholesky decomposition? A square matrix A is said to have Cholesky decomposition if it can be written as a product of a lower triangular matrix and its conjugate transpose. $latex A=LL^{*} $ If all the entries of A are real numbers, then the conjugate...

Tensor Hadamard Product using Python

In one of our previous articles, we already discussed what the Hadamard product in linear algebra is. We discussed that if A and B are two matrices of size mxn, then the Hadamard product of A and B is another mxn matrix C such that: $latex H_{i,j}=A_{i,j} \times...

Perform tensor addition and subtraction using Python

We can use numpy nd-array to create a tensor in Python. We can use the following Python code to perform tensor addition and subtraction. import numpy A = numpy.random.randint(low=1, high=10, size=(3, 3, 3)) B = numpy.random.randint(low=1, high=10, size=(3, 3, 3)) C =...

How to create a tensor using Python?

What is a tensor? A tensor is a generalization of vectors and matrices. It is easily understood as a multidimensional array. For example, in machine learning, we can organize data in an m-way array and refer it as a data tensor. Data related to images, sounds, movies,...

How to combine NumPy arrays using horizontal stack?

We can use the hstack() function from the numpy module to combine two or more NumPy arrays horizontally. For example, we can use the following Python code to combine three NumPy arrays horizontally. import numpy A = numpy.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) B =...

How to combine NumPy arrays using vertical stack?

Let’s say we have two or more NumPy arrays. We can combine these NumPy arrays vertically using the vstack() function from the numpy module. For example, we can use the following Python code to combine three NumPy arrays vertically. import numpy A = numpy.array([[1, 2,...

Singular Value Decomposition (SVD) using Python

What is Singular Value Decomposition (SVD)? Let A be an mxn rectangular matrix. Using Singular Value Decomposition (SVD), we can decompose the matrix A in the following way: $latex A_{m \times n}=U_{m \times m}S_{m \times n}V_{n \times n}^T $ Here, U is an mxm matrix....

Eigen decomposition of a square matrix using Python

Let A be a square matrix. Let’s say A has k eigenvalues λ1, λ2, ... λk. And the corresponding eigenvectors are X1, X2, ... Xk. $latex X_1=\begin{bmatrix} x_{11} \\ x_{21} \\ x_{31} \\ ... \\ x_{k1} \end{bmatrix} \\ X_2=\begin{bmatrix} x_{12} \\ x_{22} \\ x_{32} \\ ......

How to calculate eigenvalues and eigenvectors using Python?

In our previous article, we discussed what eigen values and eigenvectors of a square matrix are and how we can calculate the eigenvalues and eigenvectors of a square matrix mathematically. We discussed that if A is a square matrix, then $latex (A- \lambda I) \vec{u}=0...

Amrita Mitra

Author

Ms. Amrita Mitra is an author, who has authored the books “Cryptography And Public Key Infrastructure“, “Web Application Vulnerabilities And Prevention“, “A Guide To Cyber Security” and “Phishing: Detection, Analysis And Prevention“. She is also the founder of Asigosec Technologies, the company that owns The Security Buddy.

0 Comments

Submit a Comment

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Not a premium member yet?

Please follow the link below to buy The Security Buddy Premium Membership.

Featured Posts

Translate »