Humane Proxy

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.