Research & Security

Embedding local AI models into the development lifecycle to catch vulnerabilities before commit-time.

Applying local LLMs to assist code analysis and reverse engineering securely.

Leveraging Large Language Models to interpret binary differences, detect suspicious functions, and accelerate reverse engineering workflows.

Deploying high-interaction honeypots using lightweight containers to study attacker behavior and gather threat intelligence.

Designing a reproducible laboratory for malware behavioral baselines using rootless Podman containers and isolated networks on Arch Linux.

Effective strategies for implementing robust cyber hygiene practices in Small and Medium Enterprises with limited resources.

Strategies for hardening PHP/Laravel projects against dependency confusion and trojanized packages in the Composer ecosystem.

Creating offensive network simulation scenarios using multi-network rootless containers for secure malware execution and C2 simulation.

Rootless, Multi-Network Containers for Malware Analysis and Secure Research

An in-depth analysis of escape resilience in rootless Podman containers on Arch Linux, featuring threat modeling, stress testing, and hardening.

Evaluating the security quality of code snippets generated by AI, identifying vulnerable patterns, and defining guidelines for developers.

A pragmatic guide to implementing Zero-Trust architecture in small engineering teams without enterprise-grade budgets.