Research
Focused security research and AI adversarial testing. Vulnerabilities are consequences of design decisions—understanding them makes systems stronger.
Security Research
Vulnerability discovery, binary analysis, firmware security, web server exploitation, and responsible disclosure. Understanding where abstractions leak and design assumptions fail.
- ▸Authentication system analysis
- ▸Cryptographic usage review
- ▸Sandbox escape research
- ▸Memory corruption classes
- ▸Logic flaws & privilege boundaries
- ▸Firmware & boot chain security
AI/LLM Red-Teaming
Adversarial testing of AI systems, probing language models for vulnerabilities, studying alignment failures, and building frameworks for responsible AI security assessment.
- ▸Prompt injection & jailbreaking
- ▸Model inversion attacks
- ▸Adversarial input generation
- ▸Data leakage & extraction
- ▸Alignment failure analysis
- ▸AI system threat modeling
Research Philosophy
Research and documentation are integral to the workflow. Knowledge is something to refine and publish, not hoard. The long-term vision includes creating tools, frameworks, and knowledge bases that empower independent researchers rather than locking them into proprietary ecosystems. Ethics are inseparable from competence—the same knowledge that enables exploitation also enables defense, auditing, and improvement.