Nuclear-grade image metadata cleanser. Strip ALL EXIF/GPS/camera data, re-encode with noise injection. Forensically untraceable, reverse image search resistant.
Scanned 9/5/2026
Install to Claude Code
npx -y skills add dvcrn/openclaw-skills-marketplace --skill image-nuke --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Image Nuke?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/dvcrn-image-nuke)More formats (shields.io, HTML) on the badges page.
---
name: image-nuke
description: "Nuclear-grade image metadata cleanser. Strip ALL EXIF/GPS/camera data, re-encode with noise injection. Forensically untraceable, reverse image search resistant."
---
# Image Nuke - Nuclear Metadata Cleanser
Strip everything. Re-encode. Inject noise. Forensically untraceable.
## What Gets Destroyed
- ALL EXIF data (camera, lens, exposure, timestamps, software)
- GPS / location coordinates
- ICC color profiles
- XMP / IPTC metadata
- Adobe tags and editing history
- Embedded thumbnails
## Nuclear Operations
- Sub-pixel Gaussian noise injection (invisible to human eye)
- Micro color shift (undetectable hue rotation)
- Per-pixel brightness variation
- Random micro-crop (changes dimensions by 1-3px)
- Fresh JPEG re-encoding with randomized quality/subsampling
- Different perceptual hash (reverse image search resistant)
## Usage
```bash
# Single image - nuclear mode
python3 {baseDir}/scripts/nuke_image.py photo.jpg
# Custom output + max noise
python3 {baseDir}/scripts/nuke_image.py photo.jpg clean.jpg --noise 5
# Batch process entire directory
python3 {baseDir}/scripts/nuke_image.py --batch ./photos/ ./clean/
# Lower quality for harder reverse matching
python3 {baseDir}/scripts/nuke_image.py photo.jpg --quality 80 --noise 4
```
## Noise Levels
| Level | Sigma | Use Case |
|-------|-------|----------|
| 1 | 0.8 | Light cleanse - metadata only feel |
| 2 | 1.6 | Standard - good balance |
| 3 | 2.4 | Default - recommended |
| 4 | 3.2 | Heavy - reverse search resistant |
| 5 | 4.0 | Nuclear - maximum anonymization |
## Requirements
- Python 3
- Pillow (`pip install Pillow`)
- NumPy (`pip install numpy`)
## Notes
- Output is always JPEG (even if input is PNG)
- Original file is never modified
- Each run produces a unique output (randomized noise)
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!