# siyuanchen0214/Scam-AI-Multi-modal-Evaluation-System

Repository: https://github.com/siyuanchen0214/Scam-AI-Multi-modal-Evaluation-System
Canonical: https://ross.abutalabs.com/products/scam-ai-multi-modal-evaluation-system
Language: Python
License: MIT
License Family: permissive
Last push: 2025-11-05T01:36:42+00:00

## Health v2 (maintenance only)
Score: 39/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 50, release rhythm 35, longevity 21
- inputs: {"age_days": 302, "days_push": 302, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1001, forks 88 (observed 2026-09-03T02:15:17.921229+00:00)

## What it is
A Python-based multi-modal AI system for detecting fraudulent content across text, image, audio, and video, with provenance tracing and cross-modal consistency analysis. It includes an alert engine, signal combination strategies, and continuous learning of evolving generative patterns.

## Use cases
- detect scam content in text images audio and video
- trace the provenance of AI-generated content
- detect deepfakes across multiple modalities
- flag fraudulent social media posts automatically
- analyze cross-modal inconsistencies to spot fraud
- build an alerting pipeline for fraud signals

## When to choose
- you need multi-modal fraud or scam detection in Python
- you want provenance tracing for AI-generated content
- you need configurable alert rules over combined detection signals

## When to avoid
- you need a production-grade, commercially supported fraud platform
- you only need simple keyword-based spam filtering
- you cannot run GPU-backed ML models locally

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, nlp, image-processing, audio-processing, video-processing, computer-vision, security, alerting, analytics
- domain: artificial-intelligence, security, deep-learning, computer-vision
- platform: python, cross-platform
- tags: fraud-detection, deepfake-detection, multi-modal, provenance-tracing, scam-detection, content-authenticity, natural-language-processing, audio, video

## Member repositories
- siyuanchen0214/Scam-AI-Multi-modal-Evaluation-System (main) score 39

## Provenance
- Observed fields: from GitHub, fetched 2026-09-03T02:15:17.921229+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:16:09.583497+00:00, confidence not recorded.
  - readme: https://github.com/siyuanchen0214/Scam-AI-Multi-modal-Evaluation-System (fetched 2026-09-03T02:15:17.921229+00:00, sha 226d27a36ca5)
- Data as of 2026-08-30T08:39:29.467469+00:00.