Pixel-domain watermarks
Some systems (like Google's SynthID) modify pixel values in patterns the human eye misses but a paired detector can recover. The changes survive resizing, light compression, and color shifts.
Frequency-domain watermarks
Other approaches embed signals in the image's frequency components — the same mathematical space JPEG uses. These tend to be more robust to common edits than pure pixel patterns.
Metadata and content credentials
C2PA (Coalition for Content Provenance and Authenticity) attaches a cryptographically signed manifest to the file describing how it was made. Adobe Firefly, OpenAI, and Microsoft are early adopters.
How detection works
Detectors either look for the known statistical fingerprint of a watermark, or parse the file for provenance metadata. Check AI Watermark uses the latter approach — fast, transparent, but only effective when metadata survives.
Check AI Watermark
Upload an image to scan for AI watermarks, provenance signatures, and metadata clues.
Open Check AI WatermarkFrequently asked questions
More from this guide
What Is an AI Watermark?
Invisible signals embedded in AI-generated images, and what they actually tell you.
Read articleWhy AI Watermarks Exist
Provenance, accountability, and the policy pressure pushing every AI vendor to mark its output.
Read articleAI Watermarks vs Metadata
Embedded pixel signals and EXIF/C2PA manifests solve overlapping problems in different ways.
Read articleDetecting AI-Generated Images
Watermarks, metadata, visual artifacts, and why no single signal is conclusive on its own.
Read article