BLA
BLA (Blind LLM Agents) is the open-source Blue Defense MCP and CLI built to protect software artifacts against automated AI reverse-engineering workflows.
Can you tell a scam text, email or call from a real one? Take the free 2-minute test with realistic, AI-era examples, updated weekly from FTC alerts.
SecurityPython · JavaScriptGitHub @theguysaccountOnlineOwner unconfirmed
Have you tried it? One tap is enough. No sign-in needed.
No updates detected yet. GitHub releases will appear here.
Owners of public repositories under a personal GitHub account can sign in to verify ownership and manage the introduction themselves. No administrator approval is needed.
Sign in, generate a verification file, and commit it to this repository’s default branch within 30 minutes. Files on other branches or forks do not count. Then check the file below to manage the project without administrator approval. Keep the file to retain your access.
If needed, you will go to sign-in. After signing in, return here and press your chosen verification button again.
Run /nomorevibe verify in your project folder to verify ownership and manage the introduction yourself.
Verify in one minuteAsk about other verification options
Spot the Scam: a free 2-minute test of AI-era scam texts, emails and calls, refreshed weekly from FTC and CISA alerts. Static site, no tracking.
Taken from the repository README
Loading the full README.
Read the full README ↗Live: https://theguysaccount.github.io/psych-sec-social-engineering-defense/ · Screens: desktop and phone
A free two-minute test of the scams of the AI era. You see ten realistic texts, emails, phone calls, chats, letters and ads, and decide for each: scam or legit? Then you see the tells, highlighted in the message, and a short lesson. It's built for anyone, and especially for sending to parents.
Made by Psych Sec. Not affiliated with the FTC, CISA or any company named in examples (the names are invented).
| What | Where | When |
|---|---|---|
| Test, build, play end to end in headless Chrome, deploy, smoke-test live, IndexNow | .github/workflows/pages.yml | every push, and weekly after the refresh |
| Pull FTC, CISA and FBI alerts, tag, commit, redeploy | .github/workflows/refresh.yml | Mondays |
| Live end-to-end test, page and data health checks, keep-alive | .github/workflows/selftest.yml | Wednesdays |
Details, failure modes and the keys that switch on a custom domain, analytics and a paid team version: OPERATIONS.md.
data/types.json 25 scam types: lesson text, red flags, what to do, FTC/CISA sources, alert keywords
data/items.json the message bank (see OPERATIONS.md, "Writing items")
data/alerts.json FTC, CISA and FBI alert archive, updated weekly by refresh.yml
data/backlog.md scenario seeds for future items
pipeline/alerts.py fetch, parse, tag and merge alerts; pick the week's featured scam types
pipeline/build.py static site generator (standard library only) -> dist/
pipeline/render.py message rendering at build time (mirrors site/assets/core.js)
site/assets/ core.js (quiz logic), app.js (UI), selftest.js (end-to-end driver), site.css, og/ cards
scripts/ e2e.sh, screens.sh, og.py, indexnow.py, check_live.py, keepalive.sh
tests/ Python tests (content, alerts, build) and tests/js (logic, renderer parity)
Python 3.9+ and Google Chrome. Node 18+ for the JS tests.
python3 pipeline/build.py # build dist/
python3 -m http.server -d dist 8000 # open http://localhost:8000
python3 -m unittest discover -s tests # content, alerts, build
node --test tests/js/*.test.mjs # quiz logic, Python/JS renderer parity
scripts/e2e.sh # play dist/ end to end in headless Chrome
scripts/screens.sh # refresh docs/screens/
python3 scripts/og.py # refresh share cards after adding a scam type
Deploy is a push to main: pages.yml tests, builds and publishes to GitHub Pages.
Code: MIT (see LICENSE). Lesson text and example messages: CC BY 4.0. Alert titles and summaries are from the FTC, CISA and FBI (U.S. government works) and link to the originals.