CYBER
Research
"Seek, and ye shall find" — Matthew 7:7Independently discovering, validating, and responsibly disclosing cross-platform vulnerabilities. Authored "The Invisible Window" — 100% screen capture evasion. Motivated by reducing catastrophic risks from advanced AI.
projects
Invisible Window Research
IEEE-format research paper exposing a structural vulnerability in WebRTC-based exam proctoring. 100% evasion on Windows 10/11 and macOS 14–26 using documented OS display APIs. Responsibly disclosed to vendors.
Project Simurgh
Zero-trust integrity API connected to The Invisible Window research. Validates behavioral intent and environment integrity without relying on screen pixels, webcam frames, or invasive visual surveillance.
Project Zurvan
Local-first LLM knowledge engine. Ingests any document, extracts structured knowledge (claims, concepts, entities, decisions), and exposes it to AI agents via an MCP stdio server. 183 tests passing.
Mehr Guard
Privacy-first offline QR & URL security scanner built with Kotlin Multiplatform. 100% offline analysis with 5 platform targets.
Syllabus-Sync
AI-native Campus OS transforming university PDF syllabi into structured, agent-readable data. Full student operations suite with 503 tests across 92 files.
GitSwitch
AI-powered Git client for managing multiple identities and generating semantic commits. Built with Electron and React.
Philosophy
RESEARCH
Independently discover, validate, and responsibly disclose vulnerabilities. Measure AI capability uplift, characterise safety boundaries, and publish reproducible findings.
SECURE
Defensive applications that reduce real-world risk. Cross-platform exploit development informs better defences — offensive knowledge applied to protective systems.
Hands-on vulnerability research and AI safety experimentation. Current work: cross-platform exploit development, AI capability uplift measurement, and safety boundary characterisation.