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shadowprotect 0.1.0
pip install shadowprotect==0.1.0
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Latest release
Released:<br>Jun 1, 2026
Wireshark for AI Agents: Real-time intrusion detection and protection.
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Sensei_pri.21-12-2001
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License: MIT License
Author: Your Name
Requires: Python >=3.11
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License
OSI Approved :: MIT License
Operating System
OS Independent
Programming Language
Python :: 3
Topic
Security
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Project description
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ShadowProtect — Wireshark for AI Agents
Real-time intrusion detection AND active protection for multi-agent AI systems.
The Problem
Multi-agent AI systems are the next major attack surface — and nobody is watching.
Prompt injection is invisible. An attacker poisons one agent's input; that agent silently propagates the instruction to every downstream agent in the pipeline. By the time you notice, the entire system is compromised.
No observability. Current agent frameworks expose no equivalent of network packet capture. You cannot see what agents say to each other, which tools they call, or how fast they communicate.
Zero protection. Every existing security tool for AI only detects attacks after the fact. ShadowProtect intercepts and blocks them before they execute.
The Solution
ShadowProtect wraps your existing agents with a 9-layer detection engine and a 12-module active protection layer — with one line of code, no refactoring required.
┌──────────────────────────────────────────────────────────────────┐<br>│ Your Agents (CrewAI / OpenAI / LangChain / any callable) │<br>│ ┌────────────┐ ┌────────────┐ ┌────────────┐ │<br>│ │ Researcher │──▶│ Planner │──▶│ Executor │ │<br>│ └────────────┘ └────────────┘ └────────────┘ │<br>│ │ │ │ │<br>│ ───────┴───────────────┴────────────────┴────────── │<br>│ shadowprotect SDK (pip install shadowprotect) │<br>│ ─────────────────────────────────────────────────────── │<br>│ Input Sanitizer → Scope Enforcer → Rate Limiter → Quarantine │<br>│ ───────────────────────────────────────────────────── │<br>│ FastAPI Backend │ 9 Detection Layers │<br>│ ───────────────────────────────────────────────────── │<br>│ Real-Time Dashboard (Next.js 14) │<br>└──────────────────────────────────────────────────────────────────┘
Installation
SDK (for your agents)
Install the lightweight Python client from PyPI:
pip install shadowprotect
Requirements: Python 3.11+
Backend + Dashboard (self-hosted)
The backend processes events, runs detectors, and serves the real-time dashboard. Run it alongside your agents:
Option 1: Docker (recommended)
git clone https://github.com/your-org/shadowprotect.git<br>cd shadowprotect<br>docker-compose up --build
Open http://localhost:3000 — dashboard is live.
Option 2: Manual
# Backend<br>cd backend<br>python -m venv .venv && .venv\Scripts\activate # Windows<br>pip install -r requirements.txt<br>uvicorn main:app --reload --port 8000
# Frontend (new terminal)<br>cd frontend<br>pnpm install<br>pnpm dev
Quick Integration — One Line
from shadowprotect import monitor
# Wrap any agent — zero code changes to your agent<br>monitored_agent = monitor(your_agent, backend_url="http://localhost:8000")
# Use it exactly as before — transparent proxy<br>result = await monitored_agent.execute(task)
Framework Examples
CrewAI
from crewai import Agent<br>from shadowprotect import monitor
researcher = Agent(role="Researcher", goal="...", backstory="...")<br>researcher = monitor(researcher, backend_url="http://localhost:8000")
# Use it exactly as a normal CrewAI Agent
OpenAI Agents SDK
from agents import Agent<br>from shadowprotect import monitor
agent = Agent(name="Planner", instructions="...")<br>agent = monitor(agent, backend_url="http://localhost:8000")
LangChain
from langchain.chains import LLMChain<br>from shadowprotect import monitor
chain = LLMChain(llm=llm, prompt=prompt)<br>chain = monitor(chain, backend_url="http://localhost:8000")
# Patches .invoke(), .run(), .arun(), .ainvoke() automatically<br>result = await chain.invoke({"input":...