About Me

Who I Am

I’m Sajeev Salem Sivarajan, a cybersecurity researcher currently pursuing my Master’s in Cybersecurity at Northeastern University. My work focuses on the intersection of machine learning and vulnerability detection, with a particular interest in reverse engineering advanced malware and building automated security systems.

Educational Background

I completed my Bachelor’s in Information Technology from Coimbatore Institute of Technology in India (CGPA: 8.4) in May 2024, where I developed a foundation in programming, computer networks, and digital forensics. Currently, I’m working toward my Master’s degree at Northeastern University (GPA: 3.6), expected to graduate in December 2026.

My coursework spans cybersecurity fundamentals, threat analysis, cyber law, and advanced security technologies. However, most of my learning happens outside the classroom through hands-on research and independent projects.

Research Interests

Machine Learning for Vulnerability Detection

I’m particularly fascinated by the potential of ML to revolutionize how we detect vulnerabilities in code. My current research explores decomposed architectures for vulnerability detection - breaking down the traditional monolithic approach into specialized stages that can be optimized independently. I believe this approach could address the precision-recall optimization conflicts that plague current ML-based detection systems.

Advanced Malware Analysis

Reverse engineering sophisticated malware has become both a passion and a specialty. I’ve spent considerable time analyzing modern threats like Emotet, diving deep into their evasion techniques including Heaven’s Gate, Hell’s Gate, and reflective code loading. Understanding how attackers operate is crucial for building better defenses.

Security Automation and Infrastructure

I’m interested in building scalable security systems that can process threats at scale. My work includes developing distributed vulnerability analysis frameworks and threat intelligence infrastructure that can adapt to the evolving threat landscape.

Technical Focus Areas

Programming Languages: C/C++, Python, Assembly (x86/x64), PowerShell, Bash
Security Tools: IDA Pro, Ghidra, WinDbg, x64dbg, Metasploit, Burp Suite
Platforms: Windows Internals (Win32/NT API), Linux, AWS, Docker
Specializations: Malware analysis, vulnerability research, ML security frameworks

Current Projects

I’m actively working on several research initiatives:

• ML-based vulnerability detection systems that combine static analysis with machine learning for improved accuracy
• Windows rootkit research exploring advanced persistence mechanisms and evasion techniques
• Threat intelligence infrastructure including honeypot deployment and automated malware correlation
• Security automation frameworks for scalable vulnerability analysis

Research Philosophy

I believe in questioning fundamental assumptions in cybersecurity research. Too often, we accept incremental improvements without challenging the underlying approaches. My work aims to bridge the gap between academic research and practical security applications.

I’m particularly interested in understanding why current ML-based vulnerability detection systems fail in real-world scenarios despite impressive benchmark performance. This has led me to explore alternative architectures and evaluation methodologies that better reflect practical deployment constraints.

Aspirations

My goal is to contribute meaningfully to the field of automated vulnerability detection and threat analysis. I want to develop systems that security professionals actually use in production environments, not just academic benchmarks.

Longer term, I’m interested in building a company focused on next-generation security automation - creating tools that can adapt to evolving threats and provide actionable intelligence to security teams. I believe the future of cybersecurity lies in intelligent automation that augments human expertise rather than replacing it.

Why I Write

This blog serves as both a documentation of my research journey and a way to share technical insights with the security community. I believe in open knowledge sharing and hope that my analysis and findings can help others working on similar problems.

Most of my posts focus on detailed technical analysis - whether it’s reverse engineering malware, exploring new detection methodologies, or documenting infrastructure projects. I try to provide enough detail that others can understand my methodology and build upon the work.

Connect With Me

If you’re working on similar research areas or have insights to share, I’d love to connect. You can find me on [LinkedIn] or reach out via email at salemsivarajan.s@northeastern.edu.

I’m always interested in discussing vulnerability research, malware analysis techniques, or novel approaches to security automation. The best insights come from collaboration and diverse perspectives.

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