Overview
As a GreyMatter Operations Intern at ReliaQuest from June to July 2026, I reviewed and corrected AI-generated security descriptions and telemetry analysis for accuracy and safety before they reached customer environments. I also built security investigations within the operations team, with support from a designated technical mentor.
My hands-on work also included tuning detections, threat hunting, log integration and parsing, and developing customer recommendations. Working within the GreyMatter operations team connected these responsibilities with threat investigation, incident-response workflows, and customer-facing technical problem solving.
From question to investigative case
I investigated potential enterprise compromises by translating broad customer concerns into scoped inquiries. A customer-provided time and date range and potentially affected hosts defined the starting scope. I analyzed raw logs and telemetry from the customer’s technology, evaluated events, and built a full investigative case.
The work followed a practical sequence: define what needed to be investigated, decide what evidence to examine, analyze the events, and bring the findings together into a case and recommendations. It required making a broad question specific enough to investigate and evaluating what the available evidence supported.
Presentations and professional learning
Delivered presentations to more than 70 ReliaQuest high school interns, communicating cybersecurity concepts to an early-career audience.
I attended networking events as part of the broader professional experience. This account keeps customer identities, raw telemetry, internal detections, and security procedures confidential.
Evidence and scope
This account describes my GreyMatter Operations internship from June to July 2026: security investigations, review and correction of AI-generated analysis, and related operations work.
The company research linked below provides broader context. It is not presented as research I authored or as a measured outcome of my internship.
Connection to my broader work
ReliaQuest gives context to the questions I pursue in my own systems: what evidence supports an alert, what information a human reviewer needs, where automation can fail, and how to investigate uncertainty without overstating a conclusion.
This experience connects to my interest in applied security research: scoping an open-ended question, evaluating system evidence, and building a defensible account of what happened. In Scam Sentinel and my other projects, I explore related questions about detection, human review, and the limits of an automated decision.