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Misc42k · #4738

competition-stego-media

Lets your agent investigate steganography in media. It helps find hidden information in images, audio, or video by analyzing metadata and other hidden details.

What it does

This tool helps find hidden information within media files like images, audio, or video. It looks for secret data disguised in the technical details of the file.

When to use it

  • ✓When you suspect a media file contains a secret message.
  • ✓If you need to analyze a media file's technical details to find something hidden.
  • ✓When participating in security challenges requiring data extraction from media files.

Example of what to ask your AI

“Look for hidden information in the image file 'secret_photo.jpg'.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/zhaoxuya520/reverse-skill/blob/main/CTF-Sandbox-Orchestrator/competition-stego-media/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/zhaoxuya520/reverse-skill/blob/main/CTF-Sandbox-Orchestrator/competition-stego-media/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The tool first understands the media file's structure. Then, it examines different 'channels' within the file, such as metadata or color layers, to find the hidden data.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add zhaoxuya520/reverse-skill --skill competition-stego-media

Or download just the file:

curl -L https://raw.githubusercontent.com/zhaoxuya520/reverse-skill/main/CTF-Sandbox-Orchestrator/competition-stego-media/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Competition Stego Media

Use this skill only as a downstream specialization after $ctf-sandbox-orchestrator is already active and has established sandbox assumptions, node ownership, and evidence priorities. If that has not happened yet, return to $ctf-sandbox-orchestrator first.

Use this skill when the challenge lives inside a media container, hidden channel, or appended payload rather than a conventional crypto blob.

Reply in Simplified Chinese unless the user explicitly requests English.

Quick Start

  1. Confirm the real container type, dimensions, duration, codec, and chunk layout before guessing a hidden layer.
  2. Check metadata, thumbnails, sidecar files, and appended trailers before deeper signal-domain work.
  3. Rank candidate channels by evidence: alpha, palette, LSB, transform-domain residue, frame order, or container slack.
  4. Preserve each extracted layer separately so the transform chain stays reproducible.
  5. Stop when the hidden payload is reproduced, not merely suspected.

Workflow

1. Establish Container Truth

  • Inspect headers, chunk tables, EXIF or document metadata, container indexes, thumbnails, and file size anomalies.
  • Compare declared format against observed structure to catch polyglots, appended archives, or malformed trailers.
  • Record exact offsets, frame numbers, or channel boundaries that look promising.

2. Inspect Candidate Channels

  • Check alpha, palette order, RGB or YUV planes, LSBs, spectrogram features, document object streams, or video frame deltas.
  • Prefer evidence-driven attempts over brute forcing every transform.
  • Note whether the payload is plain bytes, another media layer, compressed data, or an encrypted blob.

3. Reconstruct The Hidden Payload Path

  • Keep the chain in order: container -> channel or carrier -> extraction -> decompression or decode -> final parse.
  • Separate extraction success from final interpretation; a channel hit is not the same as artifact recovery.
  • If the problem becomes primarily about cryptography after extraction, hand off to the broader crypto skill.

Read This Reference

  • Load references/stego-media.md for the media checklist, channel ranking guide, and evidence packaging.

What To Preserve

  • File structure facts: offsets, chunks, frame numbers, stream names, metadata keys, and trailer size
  • Intermediate extractions and the exact command or transform used to produce them
  • The final recovered payload and the channel that produced it
FAQ

What are 'channels' in a media file?

Channels are like the different parts that make up a media file, such as colors (red, green, blue), transparency (alpha), or extra information (metadata).

What is 'LSB'?

LSB stands for 'Least Significant Bit'. It's a technique where small changes in the data bits of an image or audio can hide information without the difference being noticeable to the eye or ear.

Do I need to know how to code to use this?

No, this tool is designed for non-programmers. You just need to describe what you are looking for.

Details

Original description by the author

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for image, audio, video, document, and container steganography. Use when the user asks to inspect metadata, alpha or palette channels, LSBs, thumbnails, appended trailers, QR fragments, transcoding artifacts, or recover a hidden payload from media without blind brute force. Use only after `$ctf-sandbox-orchestrator` has a

repo: zhaoxuya520/reverse-skill

Popularity

GitHub stars
42k
Ranking position
#4738
License
MIT
Updated
9/22/2026

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