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Steganography Suite

Encrypted communication hidden inside ordinary text and images.

Security Engineer and Full-Stack Developer
Independent response to a cryptography and secure-systems development brief
Complete platform prototype

The product

A full security platform that encrypts secrets and conceals them inside ordinary text or images, with measurable imperceptibility, integrity verification, detection tools, and a complete REST API.

Live product

The Steganography Pro homepage: encrypted concealment for ordinary text and images.

Live Steganography Pro homepage on ahmadyateem.pythonanywhere.com
Live productahmadyateem.pythonanywhere.com
Live Steganography Pro usage statistics and product surfaces
Live surfacesCaptured from production

Encrypted concealment for ordinary text and images, exercised end to end in a live product.

Open live product
9,600+lines across application modules, APIs, tests, and documentation
2independent carrier systems
100,000PBKDF2 derivation iterations
50+ dBimage PSNR in standard configurations
0.999+structural similarity
64 KBapproximate capacity in a 512×512 image at two bits per pixel
31REST API endpoints
94%automated test coverage across core cryptographic workflows
340 msmedian text encode/decode time
1.3 secmedian image encode/decode time

Conceal the message, not just its meaning

Steganography Suite protects a secret in two stages. The message is encrypted and authenticated first; the protected payload is then embedded inside an ordinary text or image carrier. Recovery verifies integrity so a modified carrier cannot quietly produce trusted output.

The platform supports two independent concealment systems: zero-width Unicode characters for text and least-significant-bit encoding for images. A shared product layer adds accounts, operation history, capacity guidance, analysis, challenges, a leaderboard, AI-assisted explanations, burn-after-reading messages, and REST access.

The secure path

  1. Derive key material from the password using 100,000 PBKDF2 iterations.
  2. Encrypt the message and attach an HMAC integrity check.
  3. Measure the selected carrier’s available capacity.
  4. Embed the protected payload with the appropriate text or image strategy.
  5. Analyze quality, timing, and detection signals.
  6. Extract, authenticate, decrypt, and, when applicable, reconstruct split payloads.

Capacity errors are surfaced before destructive work begins. Recovery rejects altered data instead of returning a plausible but untrusted message.

Measuring “invisible”

An image that appears unchanged to one person is not enough evidence. The suite records mean squared error, peak signal-to-noise ratio, structural similarity, capacity, encoding and decoding time, and detection confidence.

Standard image configurations achieve 50+ dB PSNR and 0.999+ SSIM. A 512×512 carrier configured at two bits per pixel holds approximately 64 KB. Text workflows complete in a median 340 ms, while image encode/decode completes in a median 1.3 seconds.

A complete platform surface

The implementation spans more than 9,600 lines across product modules, APIs, tests, and documentation, exposes 31 REST endpoints, and reaches 94% automated coverage across core cryptographic workflows.

That breadth matters because the project is not a single encoding function. It connects applied cryptography, concealment, integrity, measurable carrier quality, detection, authentication, history, and developer access into a system that can be evaluated from both a security and a product perspective.