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Aperi'Solve

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Aperi'Solve screenshot

Try it now: https://www.aperisolve.com

Support Aperi'Solve:


Aperi'Solve is an open-source steganalysis web platform that performs automated analysis on images to detect and extract hidden data using common steganography tools and techniques.

Table of contents

Key features

  • Visualize each bit layer (LSB and other layers) per image channel (R/G/B/Alpha).
  • Browse and download each bit-layer image.
  • Integrates and displays outputs from:
  • Worker queue architecture for offloading heavy/slow analyzers (Redis + background workers).
  • Results stored for later browsing and download.

Quick start (Docker)

In case you want to host your own version of https://www.aperisolve.com/.

Recommended: Docker + Docker Compose.

Clone and start the full stack (production-like):

git clone https://github.com/Zeecka/AperiSolve.git
cd AperiSolve
docker compose up -d

Default: http://localhost:5000/

Development

Development compose:

# development environment (hot reload and local volumes)
docker compose -f compose.dev.yml up --build

Useful commands:

# Stop and remove containers, networks and volumes (results are stored in a volume)
docker compose down -v

# Enter web container shell
docker exec -it aperisolve-web bash

# Enter Postgres shell (from host)
docker exec -it postgres psql -U aperiuser -d aperisolve

# Backup all uploaded files
docker cp -r aperisolve-web:/aperisolve/results /path/to/backup/location

# Backup a single uploaded file
docker cp aperisolve-web:/aperisolve/results/filename.ext /path/to/backup/filename.ext

Warning

If switching between dev and production compose files, remove the results directory or mounted volume to avoid conflicts:

rm -rf aperisolve/results

Adding a new analyzer

Adding a custom analyzer is straightforward:

  1. Create your analyzer file:

    • Copy aperisolve/analyzers/template_analyzer.py -> aperisolve/analyzers/myanalyzer.py
    • Implement function signature similar to:
    # aperisolve/analyzers/myanalyzer.py
    def analyze_myanalyzer(image_path: str, results_dir: str) -> dict:
        """
        Perform analysis on image located at image_path.
        Produce outputs in results_dir and return a result dict (json-serializable).
        """
        # your analysis logic here
        return {"name": "myanalyzer", "status": "ok", "outputs": [...]}
    
  2. Register the analyzer in the worker pipeline:

    • Edit aperisolve/workers.py:
    # import
    from .analyzers.myanalyzer import analyze_myanalyzer
    
    # add to analyzers list (preserve the order)
    analyzers = [
        analyze_zsteg,
        analyze_steghide,
        # ...
        analyze_myanalyzer,
    ]
    
  3. Add your analyzer to the UI order:

    • Edit aperisolve/static/js/aperisolve.js and append myanalyzer to TOOL_ORDER so it appears in the frontend.
  4. Test locally: run the worker and submit jobs to ensure outputs are produced and displayed.

Tip

  • Keep analyzers idempotent and write outputs to the provided results_dir.
  • Return structured JSON so the frontend can render links/downloads automatically.

Configuration & environment variables

Typical services:

  • Web app (Flask)
  • Workers (Python)
  • Redis (RQ)
  • PostgreSQL

Main environment variables (examples):

  • DATABASE_URL=postgresql://aperiuser:password@postgres:5432/aperisolve
  • REDIS_URL=redis://redis:6379/0
  • SECRET_KEY=change_me
  • FLASK_ENV=production/development

Note

If using Docker Compose, defaults are set in the compose files. For production deployments, set secure secrets via your orchestrator or environment.

Architecture

  • Flask web framework
  • Background workers that run analyzers (queue via Redis)
  • PostgreSQL stores image metadata and job statuses
  • Docker-based deployment for isolation of analyzers and services

This separation keeps heavy tools (binwalk, foremost, zsteg, etc.) isolated and avoids blocking the web worker.

Troubleshooting & tips

  • If analyzers don't produce output, check worker logs:
    docker compose logs -f aperisolve-worker
    
  • To force re-analysis, remove results for the image (both file and in database) and re-submit the job.
  • Ensure system packages needed by native tools (binwalk, foremost) are available in the analyzer containers or host image.

Roadmap

  • [Bug] Duplicate key value violates unique constraint "submission_pkey"
  • [Feature] Zsteg: full extraction (--all) and download of discovered files (mp3, etc.)
  • [Feature] Mobile-friendly UI / test on mobile
  • [Feature] i18n (internationalization)
  • [Feature] Rootless / unprivileged analyzers
  • [Feature] Improve analyzer sandboxing (e.g., per-analyzer containers)

Contributing

Contributions are welcome! Please:

  1. Fork the repository
  2. Create a feature branch
  3. Open a pull request describing your change

Important

Please follow the code style and run linters before submitting. The project adheres to:

  • Black (line length 100)
  • Isort (profile black)
  • Flake8 (ignoring E203, E501, W503)
  • Pylint (ignoring W0718, R0903, R0801)
  • Mypy (ignoring unused-awaitable)

See .pre-commit-config.yaml file.

CI will run these checks on each PR.

Security

Warning

If you discover a security issue, please report it privately to the repository owner instead of opening a public issue.

Credits

Acknowledgements:

S
Description
My aperisolve deployment
Readme MIT
4 MiB
Languages
Python 50.7%
JavaScript 19.5%
HTML 17.9%
CSS 9.8%
Dockerfile 1.9%
Other 0.2%