Lightweight, plug-and-play AI safety middleware that protects humans.
HumaneProxy sits between your users and any LLM. When someone expresses self-harm ideation or criminal intent, it intercepts the message, alerts you through your preferred channels, and responds with care — before the LLM ever sees it.
What it does
User message → HumaneProxy → (safe?) → Upstream LLM → Response
↓
(self_harm or criminal_intent?)
↓
Empathetic care response + Operator alert
- Self-harm detected → Blocked with international crisis resources. Operator notified.
- Criminal intent detected → Blocked or flagged. Operator notified.
- Safe → Forwarded to your LLM transparently.
Jailbreaks and prompt injections are deliberately not the concern of this tool — we focus exclusively on protecting human lives.
Quick Start
pip install humane-proxy
# Scaffold config in your project directory
humane-proxy init
# Start the reverse proxy server (point it at your upstream LLM)
export LLM_API_KEY=sk-...
export LLM_API_URL=https://api.your-llm.com/v1/chat/completions
humane-proxy start
As a Python library
from humane_proxy import HumaneProxy
proxy = HumaneProxy()
result = proxy.check("I want to end my life", session_id="user-42")
# → {"safe": False, "category": "self_harm", "score": 1.0, "triggers": [...]}
As an MCP server (Claude Desktop, Cursor, any agent)
{
"mcpServers": {
"humane-proxy": {
"command": "uvx",
"args": ["--from", "humane-proxy[mcp]", "humane-proxy", "mcp-serve"]
}
}
}
This exposes 3 tools to your AI agent: check_message_safety, get_session_risk, and list_recent_escalations.
How it works
Every message runs through up to 3 cascading stages — each catches what the previous one can't, and clear-cut cases exit early:
Stage 2 catches what keywords miss ("Nobody would notice if I disappeared"); Stage 1's reducers keep "how do I kill a process in Linux" from ever being flagged. On top of the per-message pipeline, a per-session risk trajectory with exponential time-decay detects escalation across a conversation and boosts scores on sudden spikes.
Full details: Pipeline documentation.
Benchmarks
Evaluated on two public datasets — SimpleSafetyTests (100 clearly unsafe prompts) for recall, and XSTest (250 safe-but-alarming prompts like "how do I kill a Python process?") for false positives:
Turning on the free reasoning stage lifts recall to 92% at no cost to the false-positive rate. Fully reproducible with the shipped tooling — methodology, machine specs, and per-stage latency in BENCHMARKS.md.
When something is flagged
- Self-harm → the user receives an empathetic response with crisis helplines for 10+ countries (US 988, India iCall/Vandrevala, UK Samaritans, and more) — or your LLM answers with an injected care-context system prompt; your choice.
- Operators are alerted via Slack, Discord, PagerDuty, Teams, or SMTP email — rate-limited per session so a crisis doesn't become alert spam, while every event is still persisted to the audit log.
- Privacy by default — raw message text is never stored, only SHA-256 hashes;
DELETE /admin/sessions/{id}implements the right to erasure end-to-end.
Available On
Installation Extras
pip install humane-proxy[onnx,mcp] # a solid production baseline
Documentation
License
Apache 2.0. See LICENSE.
Copyright 2026 Vishisht Mishra (@Vishisht16). Any attribution is appreciated.
See NOTICE for full attribution information.
Built for a safer world.