Ganesh Venkattaraman

Master of Science in Information Science (Information Security Concentration)

I’m a cybersecurity professional with a knack for solving security challenges and protecting what matters most. Whether I’m breaking stuff (legally, of course) with pen-testing, playing CTFs, or analyzing malware, I love what I do. I believe in learning every day, staying curious, and building safer, smarter digital environments.

I thrive on learning, collaborating, and staying ahead of cyber threats to build safer, stronger systems. Let’s connect and create something awesome together!

Where I’ve Made an Impact

A look at the roles where I’ve put my skills to work and learned something new every day.

March 2021 - July 2023

Securin Inc.

A cybersecurity professional with a passion for securing digital environments and solving complex security challenges. With hands-on experience in penetration testing and vulnerability assessments across diverse platforms, I developed and implemented strategies to identify and mitigate risks. My work emphasized improving system security, automating processes, and effectively communicating findings to both technical and non-technical audiences. I am dedicated to staying ahead of emerging threats and leveraging innovative techniques to safeguard digital assets. My goal is to contribute to creating safer, more resilient systems while exploring innovative approaches to protect sensitive data.

At Securin Inc., I played a key role in protecting a diverse range of clients' digital assets by leading penetration tests and vulnerability assessments across multiple environments, including web, mobile, and cloud infrastructures. My work spanned critical areas of cybersecurity, ensuring that sensitive information and systems remained secure from emerging threats.

Penetration Testing: Conducted comprehensive security assessments for web applications and mobile platforms using tools like Nmap, Wireshark, Burp Suite and Metasploit. These efforts uncovered vulnerabilities and guided security improvements.

Vulnerability Management: Performed detailed assessments to identify and analyze potential vulnerabilities, providing actionable remediation strategies to reduce risks and protect sensitive data.

Network Security: Led testing and analysis of network services, including firewalls, routers, and switches, identifying configuration weaknesses and potential attack vectors.

Cloud Security: Assisted clients in securing their cloud-based infrastructures (AWS, AzureAD) by identifying and remediating security flaws in configurations, identity and access management (IAM), and data protection policies.

Threat Analysis & Risk Assessment: Evaluated vulnerabilities and provided risk assessments based on the likelihood and impact of identified threats. Collaborated with stakeholders to prioritize critical issues, optimizing resource allocation and security improvements. This included working with tools like Qualys, Accunetix, SonarQube, NexusIQ, Netsparker (Invicti) and Tenable Nessus to prioritize risks and address critical security gaps.

Exploit Development & Red Team Engagements: Developed custom exploits and carried out red team exercises, simulating real-world attacks to assess the resilience of systems. Gained extensive experience with the MITRE ATT&CK framework.

AV Evasion: Designed and tested payloads capable of bypassing antivirus and endpoint detection systems by leveraging heuristic bypassing and process injection methods. This experience enhanced my understanding of both offensive security tactics and defensive countermeasures.

Reporting & Communication: Delivered detailed security reports to technical teams and simplified findings for non-technical stakeholders, helping organizations make informed decisions on threat mitigation and future security strategies.

March 2021 - July 2023

NetworkGeek

Fueled by a passion for cybersecurity and knowledge-sharing, I gained valuable experience in crafting practical solutions for training and development. During my internship, I created lab exercises and sandbox environments, monitored network performance, and resolved technical issues to ensure smooth training operations. I am passionate about simplifying complex technical topics and fostering practical learning experiences to enhance engagement and understanding.

During my internship, I gained hands-on experience in network monitoring, troubleshooting, and building training frameworks to enhance the skills of trainees. The role strengthened my ability to diagnose network issues and reinforced my foundation in network security principles.

Security Training Development: Designed lab exercises and sandbox environments for training on network security fundamentals. These efforts ensured participants gained practical exposure to critical concepts and tools.

Network Diagnostics: Monitored network performance and identified bottlenecks and vulnerabilities to ensure smooth operations. This included troubleshooting performance issues and recommending solutions for optimized network performance.

March 2020 - November 2020

Samsung R&D

A technology enthusiast with hands-on experience in AI and machine learning research. I contributed to cutting-edge projects by developing and optimizing algorithms for facial recognition and deploying them in resource-constrained environments. My role required innovative problem-solving and collaboration, allowing me to gain valuable insights into the practical application of advanced AI technologies. I am driven by a passion for integrating research with real-world solutions.

As a Research Intern, I contributed to AI and machine learning projects, designing models to solve real-world problems with optimized performance. My work focused on developing and deploying advanced algorithms for use on resource-constrained devices.

Deep Learning: Developed convolutional neural networks (CNN) to detect occluded faces in low-visibility environments. This enhanced the reliability and accuracy of facial recognition systems in challenging conditions.

Model Optimization: Collaborated with teams to fine-tune machine learning algorithms for deployment on edge devices. By balancing computational efficiency and accuracy, the models supported real-time applications in resource-limited environments.

Collaboration: Partnered with cross-functional teams to integrate AI solutions into practical use cases, combining research findings with industry requirements to deliver innovative outcomes.

What I Bring to the Table

Here’s what I’ve picked up along the way—From digging into vulnerabilities to crafting solutions, this is what I’m all about.

Programming Languages

Python
Rust
Go
Java
C
C++
PowerShell
Bash (Shell Scripting)
JavaScript
Assembly Language (x86)

Technical Skills

Penetration Testing
Vulnerability Management
Risk Assessment
Threat Hunting
Cyber Threat Intelligence
Network Security (Routing and Switching)
Cloud Security (AWS, Azure)
Exploit Development
AV Evasion Techniques
Digital Forensics
Incident Response
Red Teaming
Application Security

Professional Skills

Cross-Functional Team Collaboration
Problem-Solving
Critical Thinking and Decision-Making
Team Leadership and Mentorship
Time Management and Prioritization
Adaptability and Resilience
Proactive Approach to Challenges
Continuous Learning and Growth Mindset
Creativity in Problem-Solving

Projects

Some of the coolest things I’ve worked on that I’m proud to share!

Sun Tracking Turret

The Single Axis Sun Tracking Turret is a solar energy optimization system that uses an Arduino microcontroller and light-dependent resistors (LDRs) to track the sun's position. It adjusts the angle of a solar panel via a servo motor, ensuring maximum sunlight exposure throughout the day improving the overall energy output of solar panels.

Smart Garbage Management

This project provides real-time monitoring of trash levels in bins, enabling optimized waste collection. By utilizing sensors, Internet of Things (IoT) technology, and Google Maps API to find the shortest path for collection routes, enhancing urban cleanliness. This approach leads to more efficient waste management operations and improved environmental hygiene.

Robotic Arm

The 6-Axis Robotic Arm is a precision-engineered system designed for high adaptability across a variety of industrial applications. It operates using brushed DC motors paired with planetary gear mechanisms to ensure smooth and controlled motion across six degrees of freedom. Instead of traditional microcontroller-based control, the arm is operated via PLC, offering enhanced reliability and integration within automated workflows.

Autonomous Drone

Autonomous drone leverages advanced SLAM (Simultaneous Localization and Mapping) technology to autonomously navigate and map complex, GPS-denied environments. The integrated LiDAR sensor captures 3D data, enabling real-time creation of detailed point clouds. This drone is ideal for i geospatial mapping, offering unmatched efficiency and safety.

Occluded Face Detection

This project utilizes a Deep-CNN architecture built with TensorFlow to detect occluded faces and was optimized for deployment on edge devices, ensuring efficient real-time facial recognition even with limited computational resources. It earned recognition as one of the top five submissions at PRISMGlanz, a national-level hackathon hosted by Samsung.

DeepFake Detector

This project leverages the RetinaFace model to detect deepfake videos by identifying facial inconsistencies. It employs a hybrid architecture combining InceptionV3 (CNN) for extracting spatial features and GRU (RNN) for analyzing temporal sequences. This approach ensures robust detection of deepfakes by effectively capturing both visual and temporal anomalies in videos.

Vulnerability Management Copilot

An AI-powered vulnerability management tool designed to automate reconnaissance and scanning workflows. This project eliminates the need for manual CLI operations by enabling dynamic tool selection and execution through LLM prompts. From network discovery to web fingerprinting, the copilot streamlines early-stage security assessments with modular, safe Python-based automation.

Automated Prompt Injection Testing

A research-driven toolset for evaluating LLM security against prompt injection attacks. This pipeline automates red teaming across various attack intents, integrates multiple generative AI platforms, and provides structured vulnerability reports. It’s built for speed, adaptability, and deeper insights into model behavior and robustness.