This is my portfolio website

I’m a Cybersecurity student at Sheridan College. I’m passionate about cybersecurity as it is a domain which has a lot to learn and it keeps challenging me with new and interesting things. I am also very fascinated with computer systems and strive to learn more about them. I am a quick learner and a team player. I am always looking for opportunities to learn and grow. I am eager to explore new things and I am always up for a challenge, and would especially like to delve deeper into the field of cybersecurity and get a chance to develop my skills and knowledge.

My Blog

Education

Honours Bachelor of Information Sciences (CyberSecurity)

Sep ‘22 – Aug ‘26 (Expected)

Sheridan College, Oakville, Canada

3.87 CGPA (Professional)
Entrance Scholarship recipient

Professional Experience

CTF Developer

May 2024 – present

ISSessions

Sheridan College, Oakville, Canada

Collaborated in a diverse team and created challenges incorporating actual malware techniques to get the challenge takers to experience real world techniques.
Made both solo challenges and worked together in a team of 3 to create a group experience in form of multi stage challenges.

Student Researcher

Jan ‘24 – Sep ‘24

Centre for Applied AI

Sheridan College, Oakville, Canada

Worked in a team of 6 Researcher on the a Research Project titled “Objective Method for Diagnosis of Chronic Pain” in collaboration with Karmy Clinic.
Conducted research on identifying pain through facial expressions using machine learning.
Collaborated with a diverse team of researchers, fostering a collaborative environment to drive the project forward.
Worked with Pytorch and OpenFace for a deep learning model for deception detection.
Conducted comprehensive research on the software and related projects to deepen my understanding of the underlying technology and to identify innovative ideas for enhancing the software.

Certifications

TCM Security Practical Junior Malware Researcher (PJMR)
Comptia Security+
Google Cybersecurity Specialization Certificate
Working towards OSED!

Skills

Familiarity with fundamental networking principles and protocols such as the OSI model, TCP/IP, Wi-Fi, and ARP.
Skilled in Python, C, Linux Command Line, and SQL.
Knowlegde of x86 Assembly and Reverse Engineering.
Clear and organized communication, interpersonal, and organizational skills in both oral and written forms.
Capacity to tackle challenging problems due to good problem solving capabilities and manage stressful situations.
Positively exceptional customer service abilities, consistently maintaining a professional attitude.

Projects

My Attempts at Creating Shellcode

There are three different versions, each docmented and having a relevant blog post for them.
The first one was made by taking inspiration from some samples I analysed while working towards my PJMR certification.
The second one was an improvisation of the my initial attempt.
Finally, the last one was made after I researched into shellcoding practices and was able to learn how a null byte free shellcode can actually be achieved, I used a variation of this in one of the CTF challenges I helped create.

Network Packet Sniffer

A tool made using C and the socket programming API that captures network packets and displays their contents.
The tool uses raw sockets to capture packets at the data link layer and packet filtering to capture specific packets.
Allows user to filter packets based on IP address and protocol.
Helps in understanding the structure of network packets, packet headers, and packet data.
The project has provided insights into network programming, packet capturing, packet analysis, and socket programming.
Learned a lot about low-level network operations, packet sniffing, and packet filtering in linux kernel.

ARP spoofer

The project is a Python script that uses the scapy library to perform a ‘man in the middle’ attack by spoofing the MAC and IP addresses of a network device.
It allows the user to intercept network traffic between a target device and the router.
User input is taken via the command line using the argparse module to specify the target device and the router.
When terminated, the script can restore the original network configuration.
Challenges faced include learning to use the scapy library, implementing the logic for spoofing and the attack techniques, accurately addressing and modifying the fields in the network packets, and handling exceptions and errors.
The project provided learning outcomes in Python programming, network security concepts, network analysis and troubleshooting tools, and project management and documentation best practices.

Network Scanner

The project is a network scanning tool written in Python, capable of scanning IP addresses for active devices and open ports.
It uses the argparse module for user input, scapy library for sending/receiving ARP packets, and regular expressions for input validation.
The tool probes for open ports using techniques like TCP Connect Scan, Stealth Scan (TCP SYN Scan), TCP ACK Scan, TCP Window Scan, and UDP Scan.
It uses an external API to identify the manufacturer of the network interface of active devices.
The project employs multithreading to distribute the workload and speed up the scanning process.
Challenges faced include learning about network scanning techniques, implementing multithreading, understanding Python Class objects, and handling exceptions.
The project resulted in learning outcomes in Python programming, network scanning techniques, multithreading, and modularity.

Palindrome Word Checker and other cool little programs in 8086 Assembly

The project is an ongoing learning adventure in understanding how computers work at a low level, focusing on 8086 microprocessor assembly and the general x86 ISA.
Several programs have been written in assembly, including a palindrome word checker and a basic encryption algorithm.
The project features include handling I/O operations using BIOS interrupts, using the stack for data storage and retrieval, implementing program logic with branching and looping, and making code more readable with procedures and macros.
Challenges faced include understanding different memory addressing modes, proper usage of the stack, finding the right BIOS interrupt for specific operations, and managing program control flow.
The project has led to learning outcomes such as understanding assembly programming, low-level computer operations, stack operations, and BIOS interrupts of the 8086 microprocessor.
The exploration and learning in this domain continue, with interest in modern x86-64 assembly and ARM assembly.
Recently made a simple paint application in ASM, used mouse initialisation in 8086. Check it out here

Linear Regression Model

The project is a ML model created using PyTorch that implements a linear regression model using the ADAM optimisation algorithm.
The model is trained on a dataset of random data points and is capable of predicting the output for new data points.
The project uses PyTorch for creating the model, matplotlib for visualising the data and the model, and cuda tensors for tensor processing.
I have learned about gradient descent, backpropagation, optimisation algorithms, loss functions, and model evaluation.
The project has provided insights into machine learning, deep learning, PyTorch, and data visualisation.