An independent collective of AI security researchers — built for the age of advanced systems. We study emerging threats, publish findings, and share practical knowledge to strengthen the wider community.
AiMafia wasn't assembled overnight. We're an independent collective of battle-tested cybersecurity professionals studying the AI revolution as it unfolds — and documenting the risks before they scale. Our team brings decades of combined experience in offensive security, threat intelligence, red teaming, and enterprise risk management.
When the industry pivoted to AI, most security frameworks didn't follow. We did. AiMafia exists at the intersection of deep security expertise and cutting-edge AI systems research — surfacing findings, testing assumptions, and helping close the gap that legacy approaches still struggle to address.
Every week, organizations deploy new AI models, agents, and pipelines — often with little to no security validation. The attack surface is expanding faster than defenders can map it. AiMafia was formed precisely because this gap is dangerous, and most security research groups don't have the depth to close it.
AI security isn't a single checkpoint — it's a continuous research discipline that spans every phase of development, deployment, and operation. AiMafia studies how threats emerge at each stage and shares findings to help harden AI systems everywhere.
From the first architectural decision to real-time threat response in production, we track how risks evolve across the AI lifecycle and publish research to help the community harden systems at every layer — not just at the perimeter.
We probe AI systems to understand how they fail under adversarial pressure. Our research examines prompt injection, model extraction, adversarial inputs, and logic manipulation to document real-world exposure.
Training pipelines, data ingestion workflows, and model registries are high-value attack surfaces. We study the full MLOps chain — from raw data to model serving — and publish findings on how to harden it.
Standard STRIDE doesn't fully capture AI systems. We develop AI-specific threat frameworks that account for model behavior, inference risks, and supply chain vulnerabilities unique to machine learning.
We study the risks that emerge when AI runs on-device or at the edge, including model tampering, side-channel attacks, and hardware-level vulnerabilities. Our research focuses on the unique challenges of securing inference outside controlled cloud environments.

These aren't theoretical risks. They are active attack techniques being deployed against production AI systems today. AiMafia has mapped, tested, and developed mitigations for each — and we stay ahead of the evolving threat landscape so you don't have to.
Tracking emerging AI threats and looking for credible research that sharpens defensive strategy.
Building models and pipelines who want security guidance grounded in real findings and practical analysis.
Evaluating AI systems at scale and using research to identify gaps before attackers do.
Moving fast and sharing a commitment to open research, peer learning, and responsible security practices.
AiMafia: We Secure What Others Fear to Touch