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SOC Analyst

ITSOLERA PVT LTD

SOC operations focused on SIEM deployment, monitoring, and firewall integration.

• Deployed Wazuh SIEM
• Configured File Integrity Monitoring (FIM)
• Implemented pfSense software firewall
• Integrated pfSense firewall logs into Wazuh

Cybersecurity Fellowship

Buildables

A 3-month intensive fellowship program focused on practical cybersecurity skills, including threat detection, incident response, and security operations.

• Executed a controlled cyber attack simulation to validate vulnerabilities and assess organizational defense posture
• Conducted SOC monitoring and traffic analysis to detect intrusions and map Indicators of Compromise (IOCs)
• Authored incident response reports and security policies to drive strategic system hardening

IT Intern

Jauharabad Sugar Mills Pvt Ltd

Assisted in the IT department with various tasks, including network configuration, system administration, and user support.

• Assisted the CCTV installation team and helped configure OLT devices for new camera deployments
• Monitored network performance and firewall traffic using pfSense, identifying issues and ensuring stable connectivity
• Explored and worked with enterprise-level network configurations, gaining exposure to VLANs, routing, and access control
• Provided day-to-day IT support for staff, troubleshooting system, network, and hardware issues

Cybersecurity Fellowship

Bytewise

Gained practical experience in cybersecurity through hands-on projects and mentorship.

• Learned professional Cybersecurity practices
• Mentored by an Industry Professional

President

Programming Society, Sargodha University

Leading a team to organize workshops, competitions, and collaborative projects for students across all semesters.

• Leading a team to organize workshops, competitions, and collaborative projects for students across all semesters
• Mentored junior members and coordinated with faculty to align events with academic and career development goals
• Expanded active membership and introduced domain-specific tracks (Web Dev, AI, Cybersecurity)

BS in Computer Science

Sargodha University

CGPA: 3.80

• Network Security
• Information Security
• Artificial Intelligence

pfSense Firewall Security Monitoring

• Implemented pfSense software firewall and enforced network access control and traffic filtering rules
• Integrated pfSense firewall logs into Wazuh using rsyslog for centralized log monitoring
• Analyzed blocked traffic, firewall events, and security alerts via the Wazuh dashboard
• Designed secure LAN/WAN network segmentation and restricted firewall administrative access

Wazuh SIEM & File Integrity Monitoring

• Deployed and configured Wazuh SIEM (manager + agents) for centralized security monitoring
• Enabled real-time log collection (authentication, system, and application logs)
• Implemented File Integrity Monitoring (FIM) with real-time detection on critical system paths

TryHackMe - SOC L1 Capstone

• Investigated three full-chain SOC incidents (Boogeyman 1/2/3) using ELK (Elastic Stack) for log analysis and Kibana dashboards
• Performed digital forensics on email artifacts, LNK files, and malicious attachments (shortcut files, HTA, VBA macros) to trace threat actor activity
• Analyzed PowerShell logs, parsed JSON logs (with jq), and decoded obfuscated commands to reconstruct attacker behavior
• Used Wireshark to examine network captures and identified C2 (command & control) communication channels
• Conducted domain forensic investigations via Kibana: discovered privilege escalation, lateral movement, credential dumping with Mimikatz, persistence, and ransomware deployment in the final chapter

End-to-End Cyber Attack Lifecycle Analysis

• Executed a controlled attack simulation to assess security posture, utilizing offensive techniques to validate defenses and performing SOC-style monitoring to detect intrusions
• Analyzed forensic artifacts to map Indicators of Compromise (IOCs) and authored strategic security policies to drive remediation and system hardening

Machine Learning for Polymorphic Malware Detection

• Built a system to detect advanced Windows malware using behavioral analysis of API calls
• Used real malware samples and sandbox reports to train models like Random Forest and XGBoost
• Reduced false positives and improved detection accuracy with data preprocessing and model tuning
• Achieved over 96% detection rate and under 5% false positive rate on new malware