Summary
Highly analytical and results-driven Threat Intelligence Analyst with 5+ years of experience in identifying, analyzing, and mitigating cyber threats. Proven expertise in leveraging OSINT, SIEM platforms, and EDR solutions to proactively detect adversarial activity and enhance organizational security posture. Adept at developing actionable intelligence reports, collaborating with cross-functional teams, and implementing strategic defenses against advanced persistent threats.
Experience
- Led threat hunting operations, uncovering 3 previously undetected APT campaigns targeting critical infrastructure, preventing potential losses exceeding $5M.
- Developed and deployed automated threat intelligence feeds, reducing manual analysis time by 30% and improving threat detection accuracy by 25%.
- Authored 50+ detailed intelligence reports on emerging threats and vulnerabilities, directly informing C-suite decision-making and strategic security investments.
- Monitored and analyzed over 100,000 daily security events using Splunk and Recorded Future, identifying and escalating 200+ high-severity threats.
- Contributed to the development of 15+ YARA rules and Snort signatures, enhancing intrusion detection capabilities and blocking 1,000,000+ malicious attempts annually.
- Collaborated with incident response teams to provide timely intelligence, shortening average incident resolution time by 15%.
- Performed daily log analysis and vulnerability scans, identifying and remediating 50+ critical vulnerabilities in network infrastructure.
- Assisted in incident response activities, contributing to the successful containment and eradication of 10+ malware infections.
- Developed Python scripts to automate routine data collection tasks, saving approximately 5 hours per week for the security team.
Projects
- Developed a Python-based framework to automate the collection and parsing of OSINT from various public sources, including social media, forums, and dark web dumps.
- Integrated with MISP to automatically ingest and correlate IOCs, significantly reducing manual data entry and improving threat context.
- Reduced initial research time for new threats by 40% through efficient data aggregation and analysis.
- Designed and implemented a script to integrate a local malware analysis sandbox (Cuckoo Sandbox) with threat intelligence platforms.
- Automated the submission of suspicious files for dynamic analysis and extracted new IOCs, which are then pushed to SIEM for proactive detection.
- Enhanced incident response capabilities by providing rapid, in-depth analysis of unknown malware samples.
Education
- Thesis: "AI-Driven APT Detection and Attribution in Enterprise Networks"
- Achieved a GPA of 3.9/4.0.
- Graduated Cum Laude with a specialization in Network Security.
- Recipient of the Dean's List honor for 6 consecutive semesters.




