ShadowBox.py

"""
ShadowBox – AI-Powered Silent Cyberattack Simulation Tool
Python version using FastAPI, Docker, Google Cloud, OpenAI API, and CI/CD

Instructions:
1. Install dependencies:
   pip install fastapi uvicorn docker openai google-cloud-logging python-dotenv

2. Set environment variables in a .env file or your environment:
   OPENAI_API_KEY=your_openai_api_key
   GOOGLE_APPLICATION_CREDENTIALS=path_to_your_gcp_service_account.json
   GCP_PROJECT_ID=your_gcp_project_id

3. Run the app:
   uvicorn CyberSecurity:app --reload

4. Example request:
   POST http://localhost:8000/api/v1/simulation/start
   {
     "environment_image": "python:3.10-slim",
     "attack_type": "privilege_escalation"
   }
"""

import os
import uuid
from fastapi import FastAPI, APIRouter, Request
from fastapi.responses import JSONResponse
from pydantic import BaseModel
from dotenv import load_dotenv

# Load environment variables
load_dotenv()

import docker
import openai
from google.cloud import logging as gcp_logging

# Initialize OpenAI
openai.api_key = os.getenv("OPENAI_API_KEY")
GCP_PROJECT_ID = os.getenv("GCP_PROJECT_ID")

# Initialize Docker client
docker_client = docker.from_env()

# Initialize Google Cloud Logging client
try:
    gcp_logger = gcp_logging.Client(project=GCP_PROJECT_ID)
    gcp_log = gcp_logger.logger("shadowbox-simulations")
except Exception:
    gcp_log = None

app = FastAPI(
    title="ShadowBox AI-Powered Cyberattack Simulation API",
    version="1.0.0"
)
router = APIRouter(prefix="/api/v1/simulation")

class SimulationRequest(BaseModel):
    environment_image: str
    attack_type: str

@router.get("/health")
async def health():
    return {"status": "ShadowBox API is running."}

@router.get("/version")
async def version():
    return {
        "apiVersion": "v1",
        "description": "ShadowBox AI-Powered Cyberattack Simulation API"
    }

@router.post("/start")
async def start_simulation(request: SimulationRequest):
    response = {}
    container_id = None
    try:
        # 1. Create isolated Docker environment
        container = docker_client.containers.run(
            request.environment_image,
            command="sleep 30",  # Keep container alive for simulation
            detach=True,
            tty=True,
            auto_remove=True
        )
        container_id = container.id

        # 2. Simulate attack (mocked)
        attack_result = simulate_attack(container_id, request.attack_type)

        # 3. Analyze with OpenAI
        analysis = analyze_vulnerability(attack_result)

        # 4. Store results in Google Cloud Logging
        log_to_gcp(request, attack_result, analysis, container_id)

        response = {
            "container_id": container_id,
            "attack_result": attack_result,
            "analysis": analysis,
            "status": "Simulation completed successfully."
        }
        return JSONResponse(content=response)
    except Exception as e:
        response = {"error": str(e)}
        return JSONResponse(content=response, status_code=500)
    finally:
        # Clean up container if still running
        if container_id:
            try:
                container = docker_client.containers.get(container_id)
                container.stop()
            except Exception:
                pass

def simulate_attack(container_id, attack_type):
    # In real code, execute attack scripts inside the Docker container
    # Here, we just return a mock result
    return (
        f"Attack '{attack_type}' simulated on container {container_id[:12]}. "
        "Vulnerabilities found: [CVE-2023-1234, CVE-2022-5678]"
    )

def analyze_vulnerability(attack_result):
    # In real code, call OpenAI API with the attack_result as prompt
    # Here, we use OpenAI GPT-3.5/4 for demonstration
    try:
        prompt = (
            f"Given the following simulated cyberattack result, "
            f"analyze the vulnerabilities and provide recommendations:\n\n{attack_result}"
        )
        completion = openai.ChatCompletion.create(
            model="gpt-3.5-turbo",
            messages=[
                {"role": "system", "content": "You are a cybersecurity expert."},
                {"role": "user", "content": prompt}
            ],
            max_tokens=200
        )
        return completion.choices[0].message.content.strip()
    except Exception as e:
        return f"OpenAI Analysis Error: {e}"

def log_to_gcp(request, attack_result, analysis, container_id):
    if gcp_log:
        gcp_log.log_struct({
            "environment_image": request.environment_image,
            "attack_type": request.attack_type,
            "container_id": container_id,
            "attack_result": attack_result,
            "analysis": analysis
        })
    else:
        print("GCP Logging not configured. Log entry:")
        print({
            "environment_image": request.environment_image,
            "attack_type": request.attack_type,
            "container_id": container_id,
            "attack_result": attack_result,
            "analysis": analysis
        })

app.include_router(router)

# Example CI/CD pipeline (GitHub Actions: .github/workflows/ci-cd.yml)
"""
name: ShadowBox CI/CD

on:
  push:
    branches: [ main ]

jobs:
  build-and-deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Set up Python
        uses: actions/setup-python@v4
        with:
          python-version: '3.10'
      - name: Install dependencies
        run: |
          python -m pip install --upgrade pip
          pip install fastapi uvicorn docker openai google-cloud-logging python-dotenv
      - name: Run tests
        run: |
          echo "No tests yet"
      - name: Build Docker image
        run: docker build -t gcr.io/${{ secrets.GCP_PROJECT_ID }}/shadowbox:latest .
      - name: Authenticate to Google Cloud
        uses: google-github-actions/auth@v1
        with:
          credentials_json: '${{ secrets.GCP_SA_KEY }}'
      - name: Push Docker image
        run: |
          gcloud auth configure-docker
          docker push gcr.io/${{ secrets.GCP_PROJECT_ID }}/shadowbox:latest
      - name: Deploy to Cloud Run
        run: |
          gcloud run deploy shadowbox \
            --image gcr.io/${{ secrets.GCP_PROJECT_ID }}/shadowbox:latest \
            --platform managed \
            --region us-central1 \
            --allow-unauthenticated
"""

# Example Dockerfile (place in project root)
"""
FROM python:3.10-slim
WORKDIR /app
COPY . /app
RUN pip install --no-cache-dir fastapi uvicorn docker openai google-cloud-logging python-dotenv
EXPOSE 8000
CMD ["uvicorn", "CyberSecurity:app", "--host", "0.0.0.0", "--port", "8000"]
"""