AIWatermarkCheckerOpen tool

The honest hub

AI image detector — provenance edition

Most “AI image detectors” look at pixels and guess. That approach produces false accusations. The better question is: what did the model leave in the file? Here's the state of every major vendor's marking, and a reader for the parts that are publicly verifiable.

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Quick answer

As of September 2026, provenance-based “detection” beats pixel-guessing wherever vendors attach signed marks: Claude (files), OpenAI (images), Google (images), Adobe (Firefly) — all C2PA-territory. Midjourney and most open-source pipelines still leave nothing. EU AI Act transparency obligations are pushing every provider toward embedded marks, so this map keeps moving — dated, sourced, and honest.

Marking status by model family

Model familyMark on imagesMark on textThird-party verification
Anthropic ClaudeSigned C2PA credential on .png/.jpg/.svg outputsInvisible SynthID-Text-derived watermarkFiles: yes, anywhere · Text: Anthropic key only (API in private preview)
OpenAI GPT Image / DALL·EC2PA metadata in generations—Images: yes (C2PA)
Google Gemini / ImagenSynthID (pixels) + C2PA metadataSynthID-TextC2PA: yes · SynthID: Google's gates only
Adobe FireflyContent Credentials—Yes (C2PA)
MidjourneyNone by default—No provenance layer exists to check
Open-source pipelines (SD/Flux/ComfyUI)Only if the pipeline author adds it—Incorrect often; check per-file

Why we don't offer a pixel-guessing “AI detector”

Statistical pixel classifiers answer a different question (“looks AI-ish”) and are notorious for flagging human photos. Provenance answers questions with receipts: “this signed record says who made it, when, and what was done after.” Where receipts are absent we say so plainly instead of guessing — that's the product decision. For the raw-data view, use the C2PA reader, and for text work the hidden-character scanner.

Sources