ARGUS Documentation

Complete reference for the ARGUS algorithmic authenticity analysis platform. Setup, API, detection methodology, and deployment.

Overview

ARGUS analyzes any social media profile or post across LinkedIn, Reddit, Instagram, X, and Facebook and returns a trust score (0–100) with full reasoning. Flagged profiles get a public landing page indexed by Google. All analysis is framed as algorithmic opinion — not a verdict. Profile owners can dispute at any time.

Every page that goes live has been reviewed and approved by a human.

Setup & Deploy

1. Prerequisites

npm install -g wrangler
wrangler login

2. Create Cloudflare Resources

# D1 database
wrangler d1 create argus-db

# R2 buckets
wrangler r2 bucket create argus-evidence-vault
wrangler r2 bucket create argus-screenshots

# KV namespaces
wrangler kv:namespace create SCORE_CACHE
wrangler kv:namespace create RATE_LIMITER
wrangler kv:namespace create SESSION

# Queues
wrangler queues create argus-analysis-queue
wrangler queues create argus-notify-queue

3. Update wrangler.toml

Paste the IDs from step 2 into wrangler.toml.

4. Initialize Database

wrangler d1 execute argus-db --file=./schema/d1_schema.sql

5. Set Secrets

wrangler secret put ADMIN_SECRET_KEY      # Your private admin key
wrangler secret put HIVE_API_KEY          # hive.ai free tier
wrangler secret put GPTZERO_API_KEY       # gptzero.me free tier
wrangler secret put SEARCH_CONSOLE_KEY    # Google Search Console
wrangler secret put EMAIL_API_KEY         # Resend or Cloudflare Email

6. Deploy

# Deploy Worker API
wrangler deploy workers/api/index.js

# Deploy Pages frontend
cd pages && npm install && npm run build
wrangler pages deploy .next

Public API Endpoints

POST /api/analyze

Submit any URL for analysis. Rate limited: 10 req/IP/hour.

Parameter	Type	Required	Description
url	string	Yes	Profile URL to analyze
engines	array	No	Engines to run: `image`, `text`, `behavioral`, `network`, or `all`
notify_email	string	No	Email for completion notification

POST /api/submit

Community submission. Goes to admin approval queue. Rate limited: 5 req/IP/hour.

GET /api/score

Quick score lookup for browser extension. Returns cached result or auto-queues analysis.

Parameter	Type	Required	Description
platform	string	*	Platform: linkedin, reddit, instagram, x, facebook
handle	string	*	Profile handle/username
url	string	*	Full profile URL (alternative to platform+handle)

POST /api/dispute

Submit a dispute or opt-out request.

POST /api/report

Community flag for an existing profile.

GET /api/profile/:platform/:handle

Public profile data for approved/published profiles.

Admin API Endpoints

All admin endpoints require the X-Admin-Key header.

GET /api/admin/queue

Pending submissions awaiting review.

POST /api/admin/approve

Approve a submission — publishes page, triggers Google indexing, notifies submitter.

POST /api/admin/reject

Reject a submission.

POST /api/admin/dispute/resolve

Resolve a dispute — approve (remove page) or reject (keep page).

GET /api/admin/disputes

Pending disputes awaiting review.

Detection Engines

Image Engine (20% weight)

Check	Tool	Detects
GAN Artifacts	Hive AI	AI-generated faces, StyleGAN artifacts
C2PA Provenance	C2PA SDK	Missing Content Credentials, origin verification
Reverse Image	SerpAPI	Stock photos, cross-platform image reuse
EXIF Metadata	ExifTool	Stripped metadata, inconsistent camera data

Text Engine (15% weight)

Check	Tool	Detects
AI Text Probability	GPTZero	AI-generated text across bio and posts
Stylometric Variance	Custom	Unnaturally consistent writing style
Agenda Concentration	Custom	Single-topic content farming
Linguistic Patterns	NLP	Non-human linguistic markers

Behavioral Engine (30% weight)

Check	Detects
Account Age vs. Activity	New accounts with disproportionate activity
Digital Footprint	Zero pre-account digital presence
Posting Time Patterns	Robotic posting intervals
Personal Content Ratio	Absence of personal/casual content

Network Engine (35% weight)

Check	Detects
Connection Age Distribution	Networks of predominantly new accounts
Flagged Account Clusters	Connections to previously flagged profiles
Coordinated Behavior	Synchronized posting patterns across accounts

Scoring Methodology

The final trust score is a weighted aggregate of all engine scores.

Score Range	Verdict	Meaning
0 – 25	Critical	Multiple high-severity signals across engines
26 – 40	High Risk	Significant anomalies in at least two engines
41 – 60	Medium Risk	Some suspicious signals; review recommended
61 – 100	Low Risk	No significant authenticity concerns detected

Weight Distribution
Network (35%) > Behavioral (30%) > Image (20%) > Text (15%). Network analysis carries the highest weight because coordinated inauthentic behavior is the strongest indicator of fake account networks.

Database Schema

ARGUS uses Cloudflare D1 (SQLite) with six tables:

Table	Purpose	Key Fields
profiles	Analyzed accounts	trust_score, signals, risk_level, slug, status
disputes	Opt-out/challenge requests	evidence_tier, status, resolution
submissions	Incoming analysis queue	admin_status, profile_id
networks	Coordinated account clusters	coordination_score, account_count
network_members	Profile-to-network junction	network_id, profile_id
community_reports	Crowdsourced flags	profile_id, report_reason

Full schema: d1_schema.sql on GitHub

Cloudflare Services

Service	Binding	Purpose	Free Tier
D1	DB	SQLite database	5 GB + 25M reads/day
R2	EVIDENCE_VAULT, SCREENSHOTS	Immutable evidence archive	10 GB + 10M ops/month
KV	SCORE_CACHE, RATE_LIMITER, SESSION	Score cache + rate limiting	100K reads/day
Workers	—	API + pipeline orchestration	100K req/day
Queues	ANALYSIS_QUEUE, NOTIFY_QUEUE	Async job processing	1M messages/month
Pages	—	Frontend hosting	Unlimited

Browser Extension

ARGUS includes a Chrome MV3 extension that injects trust badges directly onto social media platforms as you browse.

Supported Platforms

LinkedIn — profile cards, search results, feed mentions
Reddit — post authors, user profiles
X / Twitter — tweets, user cells
Instagram — posts, profile pages
Facebook — profile pages (host_permissions only)

Installation

Clone the repository: git clone https://github.com/itallstartedwithaidea/argus.git
Open Chrome → chrome://extensions
Enable Developer Mode (top right)
Click “Load Unpacked” → select the extension/ folder

How It Works

The content script uses MutationObserver to detect dynamically loaded profile cards on SPAs. When a profile is found, it queries /api/score for the trust score. Profiles with scores below 75 get a color-coded badge injected next to the profile name. Clicking the badge opens the full analysis page.

Score	Badge	Color
≤ 25	CRITICAL	Red
26 – 40	HIGH RISK	Orange
41 – 60	MEDIUM	Amber
61 – 75	CLEAN	Green
> 75	(no badge)	—

Legal Architecture

Every published ARGUS page is protected by five elements:

“Algorithmic analysis, not a verdict” — displayed prominently on every page
Full methodology disclosure — open source, publicly auditable code
Confidence and false positive rate — transparency in scoring
Prominent dispute mechanism — above the fold, not buried
Human editorial review — every published page reviewed by admin

Language used throughout: “flagged for review”, “high risk”, “scored X/100 based on these signals” — never “fake”, “fraud”, or “criminal”.

Dispute Process

Anyone can submit a dispute at /tools/argus/dispute.html.

Tier	Evidence	Outcome
Tier 1	Government ID + platform verification	Auto-approve removal
Tier 2	Cross-platform presence, employer confirmation	Human review
Tier 3	“I am real” with no supporting evidence	Dispute denied

Resolved disputes convert the page to a “dispute resolved” notice — retained for transparency, score removed from public display. Review timeline: 14 business days.