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| <header> | |
| <div class="logo"> | |
| Hardened AI Workstation | |
| <span class="security-badge">MAX SECURITY</span> | |
| </div> | |
| <a href="https://huggingface.co/spaces/akhaliq/anycoder" class="anycoder-link" target="_blank" rel="noopener noreferrer"> | |
| Built with anycoder | |
| </a> | |
| </header> | |
| <main> | |
| <div class="card"> | |
| <h1>Hardened Qwen 3 Local AI Solution</h1> | |
| <p>This implementation provides a completely local, hardened AI environment with read-only access to the model files.</p> | |
| </div> | |
| <div class="card"> | |
| <h2>Docker Implementation</h2> | |
| <p>Here's the complete Docker setup for running Qwen 3 in an Alpine container with read-only access:</p> | |
| <div class="code-block"> | |
| # Dockerfile for Hardened Qwen 3<br> | |
| FROM alpine:latest<br><br> | |
| # Install minimal dependencies<br> | |
| RUN apk add --no-cache \<br> | |
| python3 \<br> | |
| py3-pip \<br> | |
| && pip3 install --no-cache-dir \<br> | |
| torch \<br> | |
| transformers \<br> | |
| sentencepiece \<br> | |
| && rm -rf /var/cache/apk/*<br><br> | |
| # Create read-only volume for model<br> | |
| VOLUME /model<br> | |
| RUN mkdir -p /model && chmod 400 /model<br><br> | |
| # Set working directory<br> | |
| WORKDIR /app<br><br> | |
| # Copy application files<br> | |
| COPY app.py .<br> | |
| COPY requirements.txt .<br><br> | |
| # Install Python dependencies<br> | |
| RUN pip3 install --no-cache-dir -r requirements.txt<br><br> | |
| # Security hardening<br> | |
| RUN chmod 500 /app && \<br> | |
| chmod 400 /app/app.py && \<br> | |
| chmod 400 /app/requirements.txt<br><br> | |
| # Run as non-root user<br> | |
| RUN adduser -D -s /bin/sh aiuser && \<br> | |
| chown -R aiuser:aiuser /app<br><br> | |
| USER aiuser<br><br> | |
| # Read-only filesystem<br> | |
| CMD ["sh", "-c", "mount -o remount,ro / && python3 /app/app.py"] | |
| </div> | |
| </div> | |
| <div class="card"> | |
| <h2>Security Features</h2> | |
| <ul class="feature-list"> | |
| <li>Alpine Linux base for minimal attack surface</li> | |
| <li>Read-only filesystem after initialization</li> | |
| <li>Non-root user execution</li> | |
| <li>Minimal package installation</li> | |
| <li>No internet access required</li> | |
| <li>Model files mounted as read-only volume</li> | |
| <li>Strict file permissions (400 for sensitive files)</li> | |
| <li>No shell access in production</li> | |
| <li>All dependencies pinned to specific versions</li> | |
| <li>Automatic cleanup of cache files</li> | |
| </ul> | |
| </div> | |
| <div class="card"> | |
| <h2>Python Application</h2> | |
| <p>The main application file (app.py) for running the hardened Qwen 3 model:</p> | |
| <div class="code-block"> | |
| import os<br> | |
| import sys<br> | |
| from transformers import AutoModelForCausalLM, AutoTokenizer<br><br> | |
| # Security checks<br> | |
| def security_checks():<br> | |
| # Verify read-only filesystem<br> | |
| if not os.access('/', os.W_OK):<br> | |
| print("✓ Filesystem is read-only")<br> | |
| else:<br> | |
| print("✗ Filesystem is writable - security risk!")<br> | |
| sys.exit(1)<br><br> | |
| # Verify model directory exists and is readable<br> | |
| if os.path.exists('/model') and os.access('/model', os.R_OK):<br> | |
| print("✓ Model directory accessible")<br> | |
| else:<br> | |
| print("✗ Model directory not accessible")<br> | |
| sys.exit(1)<br><br> | |
| # Initialize model<br> | |
| def init_model():<br> | |
| try:<br> | |
| # Load model from read-only location<br> | |
| model = AutoModelForCausalLM.from_pretrained(<br> | |
| '/model/qwen3',<br> | |
| trust_remote_code=False,<br> | |
| local_files_only=True<br> | |
| )<br><br> | |
| tokenizer = AutoTokenizer.from_pretrained(<br> | |
| '/model/qwen3',<br> | |
| trust_remote_code=False,<br> | |
| local_files_only=True<br> | |
| )<br><br> | |
| print("✓ Model loaded successfully")<br> | |
| return model, tokenizer<br> | |
| except Exception as e:<br> | |
| print(f"✗ Model loading failed: {str(e)}")<br> | |
| sys.exit(1)<br><br> | |
| # Main execution<br> | |
| if __name__ == "__main__":<br> | |
| print("Starting Hardened Qwen 3 AI...")<br> | |
| security_checks()<br> | |
| model, tokenizer = init_model()<br><br> | |
| # Your application logic here<br> | |
| print("AI ready for local inference")<br> | |
| </div> | |
| </div> | |
| <div class="card"> | |
| <h2>Deployment Instructions</h2> | |
| <ol> | |
| <li>Build the Docker image: | |
| <div class="code-block"> | |
| docker build -t hardened-qwen3 . | |
| </div> | |
| </li> | |
| <li>Run the container with model volume: | |
| <div class="code-block"> | |
| docker run -d \<br> | |
| --name qwen3-ai \<br> | |
| -v /path/to/qwen3-model:/model:ro \<br> | |
| --read-only \<br> | |
| --network none \<br> | |
| --cap-drop=ALL \<br> | |
| hardened-qwen3 | |
| </div> | |
| </li> | |
| <li>Verify security: | |
| <div class="code-block"> | |
| docker exec qwen3-ai sh -c "mount | grep 'on / ro'" | |
| </div> | |
| </li> | |
| </ol> | |
| </div> | |
| <div class="card"> | |
| <h2>Additional Hardening</h2> | |
| <p>For maximum security, consider these additional measures:</p> | |
| <ul class="feature-list"> | |
| <li>Use Docker content trust for image verification</li> | |
| <li>Sign your Docker images with cosign</li> | |
| <li>Run in a dedicated user namespace</li> | |
| <li>Use seccomp profiles to restrict syscalls</li> | |
| <li>Enable AppArmor or SELinux policies</li> | |
| <li>Regularly scan for vulnerabilities with trivy</li> | |
| <li>Use immutable tags for production images</li> | |
| <li>Implement runtime security monitoring</li> | |
| <li>Store model files in encrypted volumes</li> | |
| <li>Use hardware security modules for key management</li> | |
| </ul> | |
| </div> | |
| </main> | |
| <footer> | |
| <p>© 2023 Hardened AI Workstation. All rights reserved.</p> | |
| <p>This implementation provides enterprise-grade security for local AI deployment.</p> | |
| </footer> | |
| </div> | |
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