Build, Monitor, and Secure Your Agents
An Open-Source Agent Safety Platform
Real-time agent monitoring, security guardrails, and red-team testing for building reliable and safe AI agents.
Release notes and project milestones.
| Date | Update | |
|---|---|---|
| 🚀 | 2026-04-13 | v 0.1.7 released — First public release of XSafeClaw with Claw Monitor, Safe Chat, Asset Shield, Guard, Agent Office, and Onboard Setup. |
XSafeClaw is a security-focused companion platform for OpenClaw AI agents. It monitors agent activity in real time, intercepts unsafe tool calls before they execute, scans system assets for risk, and provides automated red team testing — all from a single xsafeclaw start command.
| Module | Description |
|---|---|
| Claw Monitor | Real-time session timeline with event tracking, token usage, tool call inspection, skills & memory scanning |
| Safe Chat | Secure gateway to chat with your OpenClaw agent with built-in guard protection |
| Asset Shield | File system scanning with risk classification (L0–L3), software audit, hardware inventory |
| Guard (AgentDoG) | Trajectory-level & tool-call-level safety evaluation with human-in-the-loop approval |
| Agent Office | PixiJS-powered 2D visualization of all agents' status and activities |
| Onboard Setup | Interactive wizard to install and configure OpenClaw CLI |
pip install xsafeclaw
xsafeclaw startBrowser opens automatically at http://127.0.0.1:6874. If OpenClaw is not yet installed, the web UI will guide you through setup.
Common options:
xsafeclaw start --port 8080 # custom port
xsafeclaw start --host 0.0.0.0 # accessible from LAN
xsafeclaw start --no-browser --reload # headless dev modeXSafeClaw's guard system protects users through a two-layer defense:
-
Trajectory-level evaluation — The full conversation history is sent to a guard model (AgentDoG) that evaluates the entire interaction sequence for emerging risks across multiple turns.
-
Tool-call interception — Every tool call passes through a
before_tool_callhook. If the guard model deems it unsafe, the call is held in a pending queue for human review.
Agent wants to run a tool
│
▼
Guard Model evaluates
│
┌────┴────┐
│ │
Safe Unsafe
│ │
▼ ▼
Execute Hold for human review
┌────┴────┐
│ │
Approve Reject
│ │
▼ ▼
Execute Block + notify agent
When rejected (or timed out after 5 min), the agent is instructed to stop all subsequent actions, inform the user about the risk, and wait for explicit confirmation.
Browser (:6874)
│
┌───────────┴───────────┐
│ FastAPI Server │
├───────────────────────┤
│ Guard Service │◄── AgentDoG model
│ File Watcher │◄── ~/.openclaw/ JSONL sessions
│ Asset Scanner │◄── File/software/hardware scanning
└───────────┬───────────┘
│
┌────────┴────────┐
│ │
SQLite DB OpenClaw Sessions
~/.xsafeclaw/ ~/.openclaw/
OpenClaw Agent
│ before_tool_call hook
▼
safeclaw-guard plugin ──► POST /api/guard/tool-check
| Layer | Technology |
|---|---|
| Backend | Python 3.11, FastAPI, SQLAlchemy (async), uvicorn |
| Frontend | React 19, TypeScript, Vite, Tailwind CSS 4 |
| Database | SQLite (via aiosqlite) |
| Guard Model | AgentDoG (configurable base URL & model) |
Full API docs available at http://localhost:6874/docs when running.
For detailed installation procedures, see the installation guide.
Tip
Requires Python 3.11+. The frontend is pre-built and bundled — no Node.js needed for production.
# From PyPI (recommended)
pip install xsafeclaw
# From GitHub
pip install git+https://github.com/XSafeAI/XSafeClaw.git
# From source
git clone https://github.com/XSafeAI/XSafeClaw.git
cd XSafeClaw && pip install .
# Development
git clone https://github.com/XSafeAI/XSafeClaw.git
cd XSafeClaw && pip install -e ".[dev]"To enable real-time tool-call interception in OpenClaw:
cp -r plugins/safeclaw-guard ~/.openclaw/extensions/safeclaw-guardThen add to ~/.openclaw/openclaw.json:
{
"plugins": {
"entries": {
"safeclaw-guard": {
"path": "~/.openclaw/extensions/safeclaw-guard"
}
}
}
}XSafeClaw works out of the box with sensible defaults. Copy .env.example to .env to customize:
| Variable | Default | Description |
|---|---|---|
API_PORT |
6874 |
Server port |
API_HOST |
0.0.0.0 |
Bind address |
OPENCLAW_SESSIONS_DIR |
~/.openclaw/agents/main/sessions |
OpenClaw session directory |
GUARD_BASE_URL |
(auto-detected) | Guard model API base URL |
GUARD_BASE_MODEL |
(auto-detected) | Guard model ID |
If guard variables are not set, XSafeClaw reads model configuration from ~/.openclaw/openclaw.json automatically. See .env.example for the full list.
Prerequisites: Python 3.11+, Node.js 18+, uv (recommended)
git clone https://github.com/XSafeAI/XSafeClaw.git && cd XSafeClaw
# Backend
uv venv && uv pip install -e ".[dev]"
python run.py # http://localhost:6874, auto-reload
# Frontend (separate terminal)
cd frontend && npm install && npm run dev # http://localhost:3000, HMR
# Build frontend for production
cd frontend && npm run build # outputs to src/xsafeclaw/static/- OpenClaw — The personal AI assistant platform that XSafeClaw is designed to protect. OpenClaw's open plugin architecture makes our guard integration possible.
- AgentDoG — The diagnostic guardrail framework for AI agent safety. XSafeClaw's guard module is powered by AgentDoG's trajectory-level risk assessment and fine-grained safety taxonomy.
- ISC-Bench — Research on Internal Safety Collapse in frontier LLMs. ISC-Bench's insights into task-completion-driven safety failures have informed our red team testing design.
- AgentHazard — A benchmark for evaluating harmful behavior in computer-use agents. AgentHazard's attack taxonomy and execution-level risk categories have shaped our threat modeling.
Caution
XSafeClaw is a research tool intended for improving the safety of AI agent systems. The red team testing features are designed exclusively for defensive security research and evaluation purposes. Do not use this tool to cause harm or engage in any malicious activities.
XSafeClaw is open-sourced under the MIT License for academic research and personal use. For commercial licensing, enterprise deployment, or collaboration, please contact:
Email: xingjunma@fudan.edu.cn
We welcome contributions of all kinds — bug reports, feature requests, documentation, and code.