How to detect an ARP spoofing attack on a system?

by | Mar 5, 2017 | CCNA, CCNP, CompTIA, Data Breaches and Prevention, End Point Protection, Network Security

# sudo tcpdump -vXXn -e -i eth1 dst 192.168.1.116

This means that you want to analyze packets to your IP address 192.168.1.116.

I have picked up a part of the output :

14:57:51.521068 00:1f:3a:bc:7b:58 > ****, ethertype IPv4 (0x0800), 
length 86: (tos 0x8, ttl 44, id 35883, offset 0, flags [none], proto UDP (17),
 length 72)
74.125.200.189.443 > 192.168.1.116.41334: UDP, length 44
0x0000: **** 001f 3abc 7b58 0800 4508 .H..6=..:.{V..E.
0x0010: 0048 8c2b 0000 2c11 2d1b 4a7d c8bd c0a8 .H.+..,.-.J}....
0x0020: 0174 01bb a176 0034 54a9 0087 e6d9 30be .t...v.4T.....0.
0x0030: ba35 de94 672a 603e 3fc8 5fa1 d8eb 3721 .5..g*`>?._...7!
0x0040: de39 f952 1bbf 722a 3afb 1812 2e04 6c9c .9.R..r*:.....l.
0x0050: 8a72 7d5e af95 .r}^..

Here also, you can see that 74.125.200.189 is mapped to MAC address 00.1f.3a.bc.7b.58, which is the MAC of a system that is in the local network (as per the arp-scan output).

# sudo arp-scan --interface=eth1 --localnet
Interface: eth1, datalink type: EN10MB (Ethernet)
Starting arp-scan 1.8.1 with 256 hosts 
(http://www.nta-monitor.com/tools/arp-scan/)
192.168.1.133 00:1f:3a:bc:7b:58 Pr_bc Ind.Co., Ltd.
192.168.1.138 *** (Unknown)
192.168.1.1 *** (Unknown)

Hence, the system is undergoing an ARP spoofing attack.

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 »