Research & Insights
Threat landscapes move faster than annual risk reviews. JLYPCG's Research & Insights work tracks emerging attack techniques, AI-driven threats, and sector-specific risk trends across the Asia-Pacific region—then turns that intelligence into practical guidance for the organizations we support.
Updated
July 2026
Focus Areas
Threat Intelligence: Tracking active attacker techniques, tooling, and campaigns relevant to our clients' industries. AI & LLM Security Research: Studying emerging risks in AI adoption, from prompt injection to model supply-chain exposure. Sector Risk Briefings: Translating research into practical guidance for finance, manufacturing, and public-sector clients. Vulnerability Research: Original research into misconfigurations and weaknesses across common enterprise technology stacks.
[ Capabilities ]
Why Research Matters Here
A penetration test is a snapshot; research is what keeps that snapshot current. We invest in original research so our assessments reflect how attackers actually operate today—not a checklist written two years ago. That research feeds directly into the methodology we use for every engagement.
Research that informs defense, not just headlines.
Built In-House
Where off-the-shelf tooling falls short, we build our own—custom scripts, detection logic, and automation developed in-house to test scenarios that generic scanners miss. This applied research approach keeps our assessments grounded in engineering reality, not vendor marketing.
Data Science Applied to Attack Surface Analysis
Large environments generate more log and asset data than any human team can review manually. We apply data science—Python-based analysis, pattern detection, and machine learning models—to surface the anomalies and exposure points that matter, so our offensive security work and our clients' detection teams can prioritize what actually needs attention rather than drowning in noise.
Emerging Approaches We Track
Our research team tracks approaches that are moving from theory into practice for enterprise defense:
Zero Trust Architecture — Moving away from network-location-based trust toward continuous identity verification and least-privilege access for every user and device.
Cyber Deception — Using decoys and traps to slow attackers down, increase the cost of intrusion, and generate early warning signals inside the network.
AI-Driven Adversarial Testing — Using AI to simulate realistic attack paths against a client's own environment, identifying weaknesses before real adversaries do.
Post-Quantum Cryptography Readiness — Helping clients begin planning encryption migration paths ahead of the eventual transition away from algorithms vulnerable to quantum computing.
