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Fighting AI-Automated Crime: The New Defensive Paradigm

In 2024, a finance employee in Hong Kong transferred $25M after a video call with a deepfake CFO. The attacker? An AI agent trained to impersonate, manipulate, and execute. This wasn’t some anomaly; it was a glimpse into the future—a world where autonomous AI agents are weaponized for...

Behind Financial Fraud: How Schemes Operate

Financial fraud continues to evolve faster than detection systems. As financial institutions digitize operations, fraud increasingly exploits fragmented controls and siloed data. Detection models built for isolated events struggle against coordinated campaigns. What once appeared as discrete incidents now operates as interconnected schemes spanning identities, accounts, and infrastructure—often remaining...

AI Agents and OSINT: The Future of Cyber Operations

Artificial intelligence is reshaping cyber operations. What began as basic automation and generative assistance is rapidly evolving into autonomous AI agents, often described as agentic AI systems or deployed within multi-agent architectures. These systems do more than generate content or respond to prompts. They plan objectives, execute multi-step actions, adapt...

Person of Interest Attribution: Connecting Accounts and Aliases

Finding out who stands behind an online identity is not always easy. People use many usernames, move between platforms, and change aliases often. Some accounts show little information, while others hide behind fake details. Even so, every person leaves small clues online. These clues appear in names, posts, images, writing...

Fraud Detection with OSINT: Identifying Red Flags Early

Fraud is getting harder to detect. Attackers move fast, use many platforms, and hide behind new identities. Many schemes start with small traces in public data. Strong fraud detection with OSINT helps security teams see these early clues, spot unusual activity, and react before losses happen. Fraudsters leave digital footprints...

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