Gatekeeper: Emotion‑Aware Access Control with Face Verification
What if your system could deny access not just based on who you are, but on how you feel?
Gatekeeper is a Python‑based security framework that layers real‑time face verification with emotion analysis before granting access.
How it works
- Verify identity against a reference image or an admin pool.
- Analyze emotions (anger, fear, joy, etc.) and evaluate them against a configurable policy (blocked states, thresholds, weights).
- Only grant access if both checks pass.
Why it matters
Critical operations (financial systems, secure rooms, privileged commands) deserve more than binary yes/no. By assessing emotional state, you reduce the risk of coercion, panic, or compromised decision‑making in high‑impact environments.
Get started
bash
git clone https://github.com/arpahls/gatekeeper
cd gatekeeper
python -m venv .venv
.venv\Scripts\activate # or 'source .venv/bin/activate' on Linux/macOS
pip install -r requirements.txt
python scripts/run_terminal.py
Top comments (2)
bro. exactly what i was looking for. I have tried like a dozen of similar "i built this facial recognition..." on reddit, and literally all were AI slop and buggy. this is the first one that run on the first go and worked as expected. I am now using it between my local AI inside the bootup sequence!
Hehe glad to hear that. For me it was the same case back in 2023 with ollama. I decided to make most of the 30+ custom functions around my old model public starting with the boot sequence as you say lol.