Online Image Protection & Misuse Detection Platform
SaaS that helps users protect personal photos online. Images are stored encrypted, served through tracked URLs (never raw bucket links), and continuously checked for unauthorised reuse across the web.
Upload, share, catch every misuse.
Photos upload to an encrypted library, share through tracked URLs with watermark and expiry, log every view by who/where/when, and surface unauthorised reuse on the open web with a side-by-side match and a one-click DMCA takedown.
Upload to your protected library
42 images · 2 alerts
This is an animated mockup of the image-protection capability — not a live product. Viewer emails, IPs, and the "found on" site name are illustrative; the protected image is from Unsplash.
Encrypted at rest
Images are stored in encrypted object storage. Access controls live in the platform — not in the bucket — so revoking a share takes effect immediately.
Tracked sharing URLs
Every share generates an internal tracked URL — not a raw bucket link. Every view records viewer, IP, location, and timestamp.
Watermark + view rules
Per-share watermark, expiry date, max-view count, and right-click disable. Applied at view-time so the original asset stays clean.
Per-image access log
The dashboard shows every access for every image — who viewed it, from where, when, and through which shared link.
Web-wide misuse detection
Background workers continuously check the protected library against third-party image-match services and surface unauthorised reuse with a side-by-side comparison.
DMCA action workflow
From the misuse detail, send a DMCA takedown, save evidence, or mark the use as authorised. Every action is logged in the audit trail.
SaaS that helps users protect personal photos online. Images are stored encrypted, served through tracked URLs (never raw bucket links), and continuously checked for unauthorised reuse across the web.
User uploads through a secure portal; images are encrypted at rest in object storage. Every view is served through an internal tracked URL layer — so the platform knows who viewed it, when, and from where, and can revoke access at any time. Third-party image-match APIs surface suspected reuses for the owner to review.
End users upload sensitive personal images — model portfolios, family photos, art reference, signed works — and configure who can view them. The serving layer issues tracked URLs instead of exposing raw bucket paths, so every access is logged and revocable. Background workers periodically check the user's protected library against third-party image-match services; any external usages found are reported to the owner with a screenshot and link to the offending page.
How a request flows through it
Each request enters at the top of the diagram, flows through every box, and lands at the bottom — exactly the way the production system behaves. The scan-line traces where a live request would be right now.
What it's built with
The interesting parts
Tracked URLs, not raw bucket links
Every image is served through an internal URL layer so the platform knows who viewed it, when, and from where — and can revoke access at any time without rotating bucket credentials.
Encrypted at rest
Images are encrypted at rest in object storage with access controls aligned to the platform's permission model — not just bucket-level controls.
Continuous misuse detection
Background workers check the protected library against third-party image-match APIs. Owners get a report with screenshots and links for every suspected external reuse.
Social account linking
Owners can link their social accounts so the detection layer also scans their own public profile content as the baseline, reducing false positives.
The calls that did most of the work
A handful of engineering choices shape how a system feels. Here are the ones we'd still defend — alongside what each one cost.
Internal tracked URLs over raw S3 presigned URLs
Knowing who viewed each image (and when) is the whole product. Raw S3 access bypasses that signal.
Tradeoff: Every image read goes through the application, so edge caching is harder and adds an extra hop.
Enhance the existing platform, not replace it
A working platform with paying users earns the right to incremental changes; structured enhancements ship faster and ship safer.
Tradeoff: Inherited architectural decisions in the legacy code constrain how clean the new layers can be.
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