AI-powered scam-interception and threat-intelligence service
Create an AI agent that engages scam emails while pretending to be a genuine victim, gradually elicits information about the scammers' tactics and infrastructure, and turns the resulting intelligence into profiles and indicators that security teams, threat-intelligence feeds, and law enforcement can use.
online B2B Deep Tech / Infrastructure
From IBM Technology — GPT-Red: Can AI red teams stop prompt injections? at 00:58
Problem: People who engage scammers manually may lack the skills to do so safely or collect useful intelligence. Scam-interception automation can gather information while reducing the need for untrained individuals to interact directly with scammers.
For: Security teams, threat-intelligence organizations, and law-enforcement groups that need to collect intelligence on scam operations and connect apparently separate campaigns.
Examples
- ScamBuster: planned to use AI to bait email scammers into revealing their tactics and infrastructure, with the resulting information intended for security teams, threat-intelligence feeds, and law enforcement.
Behind this: 12 build steps · 1 tool and how each is used · how to validate demand · 7 things the video never answers.
Other takes on AI security infrastructure
- Agentic consent governance layer for autonomous AI systems
- Enterprise agentic last-mile identity and access control layer
- Identity-based security infrastructure for multi-agent AI systems
- AI-agent security and control infrastructure for enterprises
- A guardrail tool that enforces strict test-driven development and other engineering rules for AI coding agents
- Secure compiler for AI-agent skills