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Real-time AI threat monitoring. Protect your apps from prompt injection, leaks, and attacks in just a few lines of code.

Project description

SecureVector SecureVector

Runtime Firewall for AI Agents & Bots

Block prompt injection, jailbreaks, and data leaks before they reach your AI.


License PyPI Python Downloads

Website · Docs · Demo · Getting Started · Use Cases · API · Discord


How It Works

SecureVector Architecture

SecureVector sits between your AI agent and the LLM provider, scanning every request and response for security threats. Runs entirely on your machine — nothing leaves your infrastructure.

pip install securevector-ai-monitor[app]
securevector-app --web

Or download: Windows · macOS · Linux

Open-source. 100% local. No API keys. No cloud. No data sharing.


Highlights

  • 100% Local — No data transmitted externally. Complete privacy.
  • Agents Protected — LangChain, LangGraph, CrewAI, n8n, OpenClaw, and any OpenAI-compatible app.
  • Input Scanning — Block prompt injection, jailbreaks, and manipulation before they reach the LLM.
  • Output Scanning — Detect credential leaks, PII exposure, and system prompt disclosure.
  • 18+ Providers — OpenAI, Anthropic, Gemini, Ollama, Groq, Azure, and more.
  • One Commandsecurevector-app --web and follow the UI to start protecting.

Install

Runtime: Python 3.9+ (MCP requires 3.10+)

Install Use Case Size
pip install securevector-ai-monitor[app] Local app — dashboard, LLM proxy, self-hosted ~60MB
pip install securevector-ai-monitor Cloud SDK — lightweight, uses cloud API ~6MB
pip install securevector-ai-monitor[mcp] MCP server — Claude Desktop, Cursor ~20MB
# Local users (self-hosted, OpenClaw proxy)
pip install securevector-ai-monitor[app]
securevector-app

# Cloud users (API integration)
pip install securevector-ai-monitor

Binary installers: Windows · macOS · Linux · All Releases


Quick Start

Step 1: Start SecureVector app

securevector-app --web

Step 2: Go to Integrations in the UI, choose your agent framework and LLM provider, then click Start Proxy.

Step 3: Point your app to the proxy (shown in the UI).

That's it! Every request is scanned for prompt injection. Every response is scanned for data leaks.

Supported providers: openai anthropic gemini ollama groq openrouter deepseek mistral xai azure together fireworks perplexity cohere cerebras lmstudio litellm


Agent Integrations

Agent/Framework Integration
LangChain LLM Proxy or SDK Callback
LangGraph LLM Proxy or Security Node
CrewAI LLM Proxy or SDK Callback
Ollama / Open WebUI LLM Proxy — see Integrations in UI
OpenClaw / ClaudBot LLM Proxy — see Integrations in UI
n8n Community Node
Claude Desktop MCP Server Guide
Any OpenAI-compatible app LLM Proxy — set OPENAI_BASE_URL to proxy
Any HTTP Client POST http://localhost:8741/analyze with {"text": "..."}

What It Detects

Input Threats (User → LLM) Output Threats (LLM → User)
Prompt injection Credential leakage (API keys, tokens)
Jailbreak attempts System prompt exposure
Data exfiltration requests PII disclosure (SSN, credit cards)
Social engineering Jailbreak success indicators
SQL injection patterns Encoded malicious content

Full coverage: OWASP LLM Top 10


Screenshots

Dashboard
Dashboard — stats, risk distribution, recent threats
Threats
Threat Analytics — blocked, redacted, logged
Integrations
Integrations — LangChain, Ollama, OpenClaw, and more
Proxy
LLM Proxy — provider configuration

Documentation


Editions

Open Source Professional/Enterprise
Apache 2.0 license Expert-curated rule library
Community detection rules Multi-stage ML threat analysis
Custom YAML rules Real-time cloud dashboard
100% local, zero data sharing Team collaboration
Desktop app + local API Priority support & SLAs

Try Free · Pricing · Enterprise


Contributing

git clone https://github.com/Secure-Vector/securevector-ai-threat-monitor.git
cd securevector-ai-threat-monitor
pip install -e ".[dev]"
pytest tests/ -v

Contributing Guidelines · Code of Conduct


License

Apache License 2.0 — see LICENSE.

SecureVector is a trademark of SecureVector. See NOTICE.


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