C2PA Content Credentials
Reads embedded content credentials and manifest data.
- Upload an image to start automatic analysis.
Meaning for the AI verdict
Waiting for analysis Free AI image detector
Free AI Image Detector — Check If an Image Is AI-Generated
Upload a photo to check if it was AI-generated, then review trusted C2PA provenance, a pixel-based AI probability, deepfake signals, and metadata.
C2PA
Browser-side read
Pixel model
Hive AI probability
Deepfake
Separate face signal
Drop an image here
JPG, PNG, WebP, or AVIF source files up to 50 MB
Image preview appears after upload
No file selected
JPG, PNG, WebP, or AVIF source files up to 50 MB
Analysis starts automatically after upload. The browser reads the original locally; only images without verified AI provenance send a resized, metadata-free JPEG or WebP copy to Hive. Hive may retain detection data for 14 days by default; its current policy and account settings control actual retention.
Analyzing image
Preparing a privacy-reduced analysis copy…
0% Automatic analysis
AI likelihood and all signal details appear when analysis is complete.
AI likelihood report
Waiting for image upload
Upload an image to start automatic analysis.
Waiting Probability this image is AI-generated
—
Waiting for analysis
Upload an image to calculate a probability
Deepfake probability
—
Deepfake is a separate face-manipulation signal; it does not by itself mean the whole image is AI-generated.
Results are an aggregation of signals, not a legal or factual final verdict. Compression, screenshots, reposting, and edits can remove watermarks or metadata.
How to read the result
0%–30% No strong AI signal; real photos and ordinary screenshots often fall here.
31%–89% Inconclusive; compression, redraws, AI edits, reposted screenshots, and mixed editing appear here more often.
90%–100% The pixel model found a strong AI signal.
100% Verified AI Not a Hive model probability; trusted signed provenance directly confirms the AI origin.
Signal breakdown
Trusted AI provenance
Confirms AI provenance only when the active Manifest is Trusted and includes an explicit generative-AI assertion.
- Automatic server analysis pending
Meaning for the AI verdict
Waiting for analysis Pixel-based AI classifier
Uses Hive pixel analysis to estimate the probability that the image is AI-generated.
- Automatic server analysis pending
Meaning for the AI verdict
Waiting for analysis Deepfake signal
Separately checks for face-swap or deepfake signals.
- Automatic server analysis pending
Meaning for the AI verdict
Waiting for analysis Basic metadata signals
Records format, size, dimensions, and cache hash evidence.
- Automatic server analysis pending
Meaning for the AI verdict
Informational only; not an AI classifier Evidence-first answer
What is an AI image detector, and how should you trust the result?
An AI image detector is a screening tool that looks for evidence that an image was generated or altered by AI. The most reliable result does not come from one score. It combines signed provenance such as C2PA Content Credentials, provider-specific watermark evidence, source history, metadata, and a pixel classifier. A valid credential can support where a file came from or how it changed; a watermark can support use of a particular provider; a classifier only estimates whether visual patterns resemble generated media. Screenshots, cropping, compression, and re-exporting can remove provenance or weaken watermarks, while edited photographs and illustrations can trigger false positives. For a practical review, keep the original file, check provenance first, inspect the source and metadata, then use visual and pixel signals as supporting evidence. Treat a missing signal as inconclusive—not proof that the image is human-made—and keep a human reviewer for publishing, moderation, copyright, or brand-safety decisions.
Reviewed by the EasyGlobe editorial team · Last updated: August 18, 2026
| Signal | What it can support | Main limitation | Decision rule |
|---|---|---|---|
| C2PA Content Credentials | Signed provenance, signer identity, and recorded edit history. | Many files have no credential, and screenshots or exports can remove it. | Verify the signature and read the actual claims; absence is inconclusive. |
| Provider watermark | Use of a supported provider or generation workflow, such as Google SynthID. | Coverage is provider-specific and no watermark is universal. | Use the provider's official verifier and report only what it confirms. |
| Source history | Earlier appearances, publishers, and visually similar versions on the web. | The earliest indexed copy may not be the original creator. | Compare early sources and context before making an origin claim. |
| File metadata | Device, software, dimensions, timestamps, and export clues. | Metadata is easy to strip, rewrite, or inherit from later editing. | Prefer the original file and treat metadata as supporting context. |
| Pixel classifier | A probability that visual patterns resemble AI-generated media. | False positives and false negatives remain possible. | Use the score as one signal; confirm it with provenance and source evidence. |
How the detector works
The workflow starts with the strongest deterministic signals before using heavier model-based checks. It is designed for reviewers who need a fast first pass, not a final legal ruling.
Last updated: August 18, 2026
1. Provenance
Read C2PA first
The browser reads embedded Content Credentials before upload. A Trusted credential can identify the signer and claim generator; only a structured generative-AI assertion confirms AI provenance.
2. Pixel model
Estimate AI probability
After local provenance review, Hive analyzes a resized, metadata-free copy and returns an AI-generation probability. This is a model estimate, not a watermark or factual proof.
3. Deepfake
Keep face manipulation separate
A separate score checks face-swap or deepfake risk. It does not mean the entire image was generated by AI, so the interface never merges it into the general AI probability.
Methodology and signal hierarchy
AI image detection is most reliable when the tool separates cryptographic provenance, pixel-model estimates, deepfake risk, and ordinary metadata. This page uses that hierarchy so a missing signal does not get mistaken for proof that an image is human-made.
High confidence
A Trusted C2PA credential whose active Manifest contains an explicit structured generative-AI assertion is the strongest result because it provides signed provenance rather than a visual guess.
Medium confidence
A Hive AI probability of 90% or higher is reported as likely AI-generated, but remains a probabilistic model result rather than verified provenance.
Low confidence
Scores between 30% and 90% remain inconclusive. The tool exposes the score instead of forcing a binary answer from ambiguous evidence.
No strong AI signal
A score of 30% or lower means the current model found no strong AI signal. It does not prove the image is authentic, human-made, or unedited.
Learn how to identify AI-generated images
Use the detector for a fast first pass, then follow a repeatable verification workflow or compare tools for higher-risk reviews.
What each detection channel means
The tool reports every channel separately because different AI image generators leave different traces. Provenance, a pixel-based probability, and face manipulation evidence answer different questions.
C2PA Content Credentials
Checks for signed provenance data embedded in the file. When present, it can describe origin, edits, ingredients, and claim generator information.
Trusted provenance
Requires a Trusted C2PA manifest plus an explicit structured generative-AI assertion before confirming AI provenance. Valid means the signature is intact but the signer is not trusted, so it does not override the model.
Pixel-based AI probability
Hive evaluates visual patterns and returns a probability from 0% to 100%. The likely-AI threshold is deliberately conservative at 90%.
Deepfake signal
Checks for face swaps or AI-manipulated faces separately. A high deepfake score does not prove that the rest of the image is synthetic.
Generator candidates
When available, the model surfaces up to three likely generator families. These are supporting scores, not attribution proof.
Basic metadata
Records file type, size, and dimensions. A private hash supports cache lookup but is not exposed in the public response.
Limits you should expect
AI image detection is a signal aggregation problem. Screenshots, cropped images, social media recompression, format conversion, and manual retouching can remove metadata or weaken invisible watermarks.
Model-based detectors also have false positives and false negatives. A polished illustration, 3D render, stock photo, or heavily edited camera image can resemble generated media even when it is not.
Use high-confidence signals to support review decisions, and keep inconclusive results in a human review workflow when the image has legal, brand safety, editorial, or moderation consequences.
Privacy and upload handling
Browser-side C2PA detection runs against the original before server analysis. Pixel analysis sends only a resized, metadata-free JPEG or WebP copy to the site API and Hive.
Source images can be up to 50 MB. The browser resizes the longest edge to 2048px and keeps the analysis copy within the 10 MB server limit, with a separate pixel-count guard for unusually large images.
The API uses a private SHA-256 digest for 30-day cache lookup. Repeated checks reuse the result without another paid model call, and the digest is not returned publicly.
Focused watermark checks
If your review is specifically about AI watermark evidence, these focused pages separate Google SynthID, C2PA, and general watermark intent from broader AI image detection.
Reference sources
These references explain the standards and platform constraints behind the detector design.
C2PA Content Credentials specification
The current technical specification for cryptographically verifiable content provenance.
Content Credentials Verify
An official verification surface for inspecting C2PA credentials in a file.
Google DeepMind SynthID
Google's official description of SynthID watermarking, supported media, and verification paths.
Google About this image
Explains how to inspect earlier appearances, similar images, and available creation details.
OpenAI C2PA in ChatGPT Images
Documents OpenAI's C2PA implementation and why missing metadata is not proof of human origin.
Hive AI-generated content detection
The provider's description of the pixel-classification signal used by EasyGlobe.
AI image detection FAQ
Practical limits and privacy details for image verification.
No detector can prove that in every case. This tool separates validated provenance, a pixel-based AI probability, deepfake signals, and metadata so reviewers can make a better decision with context.
C2PA Content Credentials are signed provenance records embedded in media files. When present, they can show the tool, signer, and process used to create or edit an image.
Screenshots, compression, social platform reposting, and manual editing can strip metadata or damage invisible watermarks. Some generators also do not publish detectable provenance.
The browser reads C2PA from the original locally first. Pixel analysis sends only a resized, metadata-free JPEG or WebP copy to the site API and Hive.