Aegis Guardian
A free, bilingual (English / Español) AI scam shield for everyday people and their families.
Un escudo gratuito y bilingüe contra estafas, hecho para las familias.
Paste a suspicious text, email, or phone number, or upload a screenshot. Aegis tells you if it's likely a scam, shows you the red flags, and tells you what to do next, in plain English or Spanish.
Aegis is a consent-first personal safety and anti-scam agent, built so it can never become the surveillance tool it's meant to prevent. It's part of the Guardian security portfolio, alongside VPN Guardian and Wi-Fi Guardian. Like its siblings, it's open source and auditable, so you can verify there's no hidden backdoor.
Live: try the scam checker in English or Spanish. AI layer powered by Meta's Muse Spark.
Why this exists
Scams, not hacks, are where people lose the most money:
- $20.9 billion in cybercrime losses were reported to the FBI in 2025, a record, from over 1 million complaints.
- 85% of those losses came from cyber-enabled fraud: scams, not break-ins.
- People 60 and over lost $7.75 billion, up 59% in one year.
- Phishing and spoofing was the most reported crime type.
- AI-related complaints were counted for the first time: 22,364 complaints and $893 million lost.
Source: FBI IC3 2025 Internet Crime Report (April 2026).
Data breaches make it worse. Leaked personal info lets scammers write texts that mention your real name, bank, or recent order. Existing scam checkers mostly give a yes/no answer, in English, behind a paid antivirus plan.
Aegis is different:
- Bilingual by default. Spanish-speaking families are heavily targeted and underserved.
- Explains the why. It teaches people the red flags so they get better at spotting scams on their own.
- Family-first. It turns a scam into a shareable warning card you can send to your group chat.
- Free and open source. No upsell, ever.
Most "family tracking" apps quietly cross the line into surveillance. Aegis is the opposite bet: a safety tool people install because it protects them, built transparently enough that they can trust it.
How the scam scanner works
Aegis uses two layers. A fast, local rule engine (already shipped, see app/scam/) catches known patterns with no network at all. The AI layer reads what rules can't: screenshots, new scam scripts, and context.
Screenshot / text / number
│
▼
┌─────────────────┐
│ Rule engine │ local, instant, no network
│ (scam_shield.py)│ known scam patterns + scoring
└────────┬────────┘
│
▼
┌─────────────────┐
│ Muse Spark │ reads the message or screenshot, reasons about
│ (Meta Model API)│ red flags, searches for reports on the sender
└────────┬────────┘
│
▼
┌─────────────────┐
│ Verdict card │ 🔴 Likely scam / 🟡 Suspicious / 🟢 Looks safe
│ │ + red flags found + what to do next (EN/ES)
└────────┬────────┘
│
▼
┌─────────────────┐
│ Muse Image │ optional "Anatomy of this scam" warning card
└─────────────────┘ to share with family
Red flags Aegis checks for
- Fake urgency ("your account will be closed in 24 hours")
- Look-alike or shortened links
- Spoofed senders (banks, USPS, toll agencies, the IRS, Amazon)
- Requests for gift cards, crypto, wire transfers, or payment apps
- Requests to text a different number or move to WhatsApp, Telegram, or another app
- Fake recruiter "task scams" and too-good-to-be-true pay
- "Wrong number" openers and investment offers
- Impersonation of family ("Hi mom, this is my new number" / "Hola mamá, este es mi nuevo número")
- Spanish-language versions of job, urgency, and payment scams
Try it now
In your browser: jeffreyesdavid.github.io/aegis-guardian/app. English and Spanish, runs entirely on your device.
From the terminal:
python3 app/scam/scam_shield.py --file app/scam/samples/scams.txt
Tests: cd app/scam && python3 -m unittest (23 tests) and node app/scam/test_parity.mjs (checks the browser and Python engines agree).
Built with
| Tool | Role in Aegis |
|---|
| Python rule engine | Local, offline first pass (app/scam/) |
| Muse Spark (Meta Model API) | AI scanner: reads text and screenshots, reasons about red flags, web-search grounding |
| Muse Image | Generates shareable scam warning cards |
| SAM 3.1 | Experimental: "X-ray mode" to highlight suspicious parts of a screenshot |
| Muse Code | AI coding agent used to build the project |
This is the beginning of the README. Read the rest at the original. Read the full README ↗
