AI-Driven Pirated Asset Detection

Canary will find your pirated assets on the web using machine learning pipelines, automation systems, and multi-agent solutions designed to reduce costs, improve security, and accelerate operational efficiency.

See Canary in Action

Canary identifies piracy signals across multiple networks and presents timestamped, corroborated evidence for publisher review.

Mirrors Confirmed
3
Networks Detected
2
First Seen
20 days ago

Crossref Metadata

Title: Advanced Detection Strategies for Scholarly Piracy Networks

DOI: 10.1234/canary.demo.2026.001

Authors: Mitchell, Carter

Publisher: Sample Publisher

Published: 2025-11-18

Pirate Site Results

Libgen

Found on libgen.is, libgen.rs, libgen.li
First seen: 2026-03-12 08:42:10
Last seen: 2026-03-31 09:17:44
Added to libgen on: 2026-03-11 21:05:00 (20 days ago)
Appeared on libgen: 114 days after publication

Scihub

Found on sci-hub.st, sci-hub.red
First seen: 2026-03-29 13:20:54
Last seen: 2026-03-31 09:18:10

Annas

Not found
No matching DOI signal found on checked mirrors.

Zlibrary

Inconclusive z-library.sk
One mirror responded, but the result could not be confirmed automatically.
Last historical sighting: 2026-03-30 20:12:33

Pdfdrive

Not found
No matching asset metadata found on checked mirrors.
Access Canary

What Canary Delivers

Targeted Detection

Searches known piracy ecosystems using DOI-led identification instead of noisy keyword matching.

Evidence-Based Results

Presents first seen, last seen, mirror corroboration, and source-specific result states.

Publisher-Focused Workflow

Built to support review, escalation, and enforcement workflows without exposing unsafe retrieval behavior.

Searching selected sources…
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