AI-Powered Detection and Reporting of Sponsored Scam Ads on Social Media Using Hashtag Intelligence and Content Analysis for Law Enforcement Action

AI-Powered Detection and Reporting of Sponsored Scam Ads on Social Media Using Hashtag Intelligence and Content Analysis for Law Enforcement Action

Objective

The primary objective is to build a comprehensive AI-driven fraud simulation and escalation platform that replicates the real-world workflows of cybercrime reporting, classification, and inter-agency coordination. The solution is designed to simulate how digital evidence—such as suspicious messages or multimedia—is identified, analyzed, and acted upon by law enforcement and regulatory bodies including telecom authorities (DOT), banks, payment gateways, and social media platforms. It utilizes modular AI agents to automate fraud classification, extract scam patterns, initiate communication with nodal officers, and intelligently update suspect profiles based on multi-source feedback, thereby enabling full-cycle testing of cybercrime case handling under realistic constraints and data conditions.

Scope

The solution encompasses the complete lifecycle of cyber fraud detection, escalation, and intelligence updating through the integration of AI agents, structured master data, and inter-agency workflows. It leverages legal document templates, telecom metadata, banking formats, social media records, and tagged suspicious messages to simulate real-world scenarios. AI agents classify suspicious content, identify decoy group members, extract scam patterns and targeted entities, and auto-generate formal escalation emails to nodal officers across DOT, banks, payment gateways, and social media platforms. System agents handle email dispatch and reception, parse incoming responses, and trigger updates to user profiles through secure APIs, including risk scoring, case linkage, and activity logging. The platform supports a variety of fraud types, from phishing and impersonation to coordinated multi-platform scams, and includes mechanisms to simulate edge cases like unresponsive agencies and email bounces. Designed for flexibility, realism, and intelligence automation, the system serves as a robust testbed for validating end-to-end investigative operations.