Cybersecurity Researcher Ii
Current• Orchestrated the automation of monthly reporting, reducing processing time from weeks to seconds using Python, Matplotlib, NumPy, PostgreSQL integration (Psycopg2), and dynamic report templates• Employed advanced Artificial Intelligence (AI) technologies, including Large Language Models (LLMs), on internal and AWS EC2 servers to generate insightful reports from historical PostgreSQL data. • Integrated LLMs/AI into internal tools for proactive threat actor communication analysis, strengthening security measures• Developed an advanced external honeypot utilizing Flask, JavaScript, and modern web technologies to precisely log critical data points, capturing threat actor locations, IP addresses, User Agent (UA) strings, and visit counts• Engineered a specialized Python module using Pandas and Matplotlib to streamline charting processes within the research team, replacing scattered code and facilitating smoother data visualization across the organization• Spearheaded the development of robust Python APIs with Flask, enabling complex queries for efficient bulk extraction of critical company data, significantly enhancing operational efficiency• Conducted in-depth analysis on customer-submitted suspicious links and files, generating detailed reports to heighten awareness of associated risks and improve security consciousness• Strengthened organizational security by proactively reviewing and validating rules governing customer emails, leveraging internal applications to assess threat levels and protect customers from malicious emails.• Utilized comprehensive data analysis to produce supplementary reports and engaging visual representations based on intelligence gathered by the Threat Intelligence team• Administered Amazon Web Services (AWS) infrastructure, managing EC2 instance deployment while enhancing security protocols through policy updates. Utilized AWS expertise to maintain a secure and efficient system, ensuring smooth operations and data protection
