🟢 Open to work
I practice real-world IoT attack and defense techniques through an externship, learning both offensive tests and practical defenses.
My portfolio centers on hands-on IoT cyber defense work: attacking device chains, documenting attack vectors, and producing security playbooks with recommended mitigations.
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Hydroficient · ✅ Verified by Extern · ⏱️ In progress
Build, hack, and defend real IoT infrastructure, then hand your security playbook to an actual company. You’ll launch realistic cyberattacks, from spoofing and replay attacks to unauthorized shutoffs, and implement defenses like TLS and mTLS.
Developing a host-based endpoint monitoring tool in Python that tracks real-time socket states via the macOS kernel and parses netstat data to alert on unauthorized external established connections
Engineered a privacy-centric automation script in Python that streams raw server authentication telemetry into a locally hosted LLM (Ollama + Llama 3.1) to analyze real-time log anomalies and flag brute-force signatures while preserving full data privacy; Implemented programmatic data pre-filtering logic to strip background network noise, reducing LLM context overhead and optimizing compute speed
Engineered a multi-threaded network reconnaissance tool in Python (socket, threading) with a thread-safe queue that scaled scanning to audit 1,024 ports in 0.09 seconds; Automated analysis of connection handshake status codes to map exposed access vectors and identify potential attack surfaces
Built an automated cloud infrastructure risk evaluation tool in Python (AWS SDK / Boto3) that continuously maps identity security baselines and flags over-privileged accounts, inactive access keys, and non-MFA compliant endpoints
Captured and analyzed live network traffic to identify anomalies and support troubleshooting of network and system behavior
I practice real-world IoT attack and defense techniques through an externship, learning both offensive tests and practical defenses.
I am a junior at George Mason University pursuing a bachelors degree. I have limited professional experience and I'm building practical skills through hands-on projects, including an IoT cyber defense externship focused on attacking and defending real devices and networks.
Externships
Hydroficient IoT Cyber Defense Externship
In progress
Experience
Cybersecurity Extern
Hydroficient IoT Cyber Defense Externship · Sep 2026 – Present
Hostess
Ashby Ponds Senior Living · Jan 2024 – Present
Cyber Security Intern
CCI Program, CIA / NRO · Jun 2023 – Aug 2023
Education
George Mason University, Fairfax, VA
B.S. in Cyber Security Engineering
Skills
✅ Verified by Extern · ⏱️ In progress
Build, hack, and defend real IoT infrastructure, then hand your security playbook to an actual company. You’ll launch realistic cyberattacks, from spoofing and replay attacks to unauthorized shutoffs, and implement defenses like TLS and mTLS.
The work simulated an IoT security analysis of a marina's smart-device network. It mapped system components, applied the STRIDE framework to enumerate threats, and produced a threat-model PDF plus a one-page threat-model card that prioritized risks and listed mitigation recommendations.
I produced a threat-model PDF and a one-page threat-model card that documented mapped components, STRIDE-identified threats, and prioritized mitigation recommendations.
During the Grand Marina externship I mapped system components, applied STRIDE to identify threats, and produced a threat-model PDF plus a one-page threat-model card detailing prioritized risks and mitigation recommendations.
The module required building a mock sensor. I wrote a Python sensor log generator that simulated timestamped water-sensor readings, added realistic variation and anomalies, and produced CSV/JSON logs for analysis. The submission included runnable Colab and a hosted log file.
Developing a host-based endpoint monitoring tool in Python that tracks real-time socket states via the macOS kernel and parses netstat data to alert on unauthorized external established connections
Engineered a privacy-centric automation script in Python that streams raw server authentication telemetry into a locally hosted LLM (Ollama + Llama 3.1) to analyze real-time log anomalies and flag brute-force signatures while preserving full data privacy; Implemented programmatic data pre-filtering logic to strip background network noise, reducing LLM context overhead and optimizing compute speed
Engineered a multi-threaded network reconnaissance tool in Python (socket, threading) with a thread-safe queue that scaled scanning to audit 1,024 ports in 0.09 seconds; Automated analysis of connection handshake status codes to map exposed access vectors and identify potential attack surfaces
Built an automated cloud infrastructure risk evaluation tool in Python (AWS SDK / Boto3) that continuously maps identity security baselines and flags over-privileged accounts, inactive access keys, and non-MFA compliant endpoints
Captured and analyzed live network traffic to identify anomalies and support troubleshooting of network and system behavior
