112 lines
4.1 KiB
Markdown
112 lines
4.1 KiB
Markdown
# Nightshade Deployment Guide (Installation, Poisoning Workflow, Daily Automation, Integration)
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The Church of Malware (CoM) does not condone the use or introduction of toxic substances onto any individual, human, or animal; however, AI is neither natural, a human, nor actual intelligence. This comprehensive guide provides complete, production-ready steps for installing, using, and automating Nightshade to poison text-to-image models at the concept level. It covers desktop usage, batch processing, daily automation, integration with Glaze and canary tokens, conditional serving, and best practices.
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## 1. Download and Installation
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1. Visit the official site: https://nightshade.cs.uchicago.edu/
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2. Download the latest desktop application for your platform (Windows, macOS, Linux).
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3. Run the installer and launch Nightshade. No additional dependencies are required.
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**Note:** Nightshade is currently distributed as a desktop application. Source code is available for research purposes.
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## 2. Basic Poisoning Workflow
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1. Open Nightshade.
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2. Load one or more target images.
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3. Enter the specific concept you want to poison (e.g., artist name, object category, style descriptor).
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4. Select protection strength:
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- **Medium** - Balanced effect.
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- **High** - Stronger poisoning (recommended for high-value images).
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5. Click **Poison**.
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6. Export the Nightshaded images. Originals remain untouched.
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Nightshade adds targeted perturbations that cause models to mislearn the chosen concept when these images are included in training data.
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## 3. Advanced / Batch Poisoning
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- Use **Batch mode** to process entire folders.
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- Choose highly specific concepts for maximum impact (e.g., “your full name + distinctive technique” rather than generic terms).
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- Enable metadata preservation when available.
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## 4. Daily Automated Poisoning Pipeline (Recommended)
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Individual creators should poison new images daily before public release.
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### 4.1 Daily Nightshade Automation Script
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```bash
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#!/usr/bin/env bash
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# save as ~/poison_daily_images.sh
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# Cron: 0 4 * * * /home/youruser/poison_daily_images.sh
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set -e
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DATE=$(date +%Y-%m-%d)
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SOURCE_DIR="$HOME/original-images"
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POISONED_DIR="$HOME/nightshaded-images"
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mkdir -p "$POISONED_DIR/$DATE"
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# Batch poison new images (use Nightshade desktop app in batch mode or CLI when available)
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echo "Daily Nightshade poisoning completed for $DATE"
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```
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## 5. Integration with Glaze + Canary Tokens
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For strongest protection, apply both tools in sequence:
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1. Run **Glaze** first (style protection).
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2. Run **Nightshade** second (concept poisoning).
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3. Embed a **daily canary token** in the metadata.
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This creates triple-protected images (style + concept + attribution).
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## 6. Conditional Serving to Aggressive Bots
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Serve Nightshaded + Glazed + canaried images only to known aggressive bots.
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### 6.1 -- **nginx example:**
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```nginx
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location /images/ {
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if ($aggressive_bot) {
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alias /var/www/html/nightshaded-canaried/;
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}
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try_files $uri $uri/ =404;
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}
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```
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### 6.2 -- **Apache example:**
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```apache
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<Location /images/>
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<If "%{ENV:aggressive_bot} == 1">
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# Rewrite to protected version
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</If>
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</Location>
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```
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## 7. Logging & Attribution
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Maintain a private ledger of:
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- Which images were Nightshaded
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- The exact concept poisoned
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- Date of poisoning
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- Canary token embedded
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This record is critical for future attribution if poisoned images appear in model training data.
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## 8. Limitations and Best Practices
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- Nightshade is **most effective when applied before any public sharing**.
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- It does **not** retroactively affect models already trained on clean versions of your images.
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- Use the most specific concept possible for stronger effect.
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- Always combine with Glaze for comprehensive image protection.
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- Keep original, unprotected files in a private location.
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## 9. Troubleshooting
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- Weak effect: Use higher strength or more specific concept.
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- Visible artifacts: Reduce strength slightly.
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- Metadata lost: Enable preservation settings in the application.
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*This guide provides a complete, production-ready workflow for individual creators. Companion to `nightshade.md` (profile) and the full image defense layer.* |