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AI image detection

The Image Detector reads an image through complementary model, forensic and source-signature checks. The combined report keeps the main probability and the strongest evidence together.

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Asynchronous job lifecycle

  1. Upload

    The signed-in web route validates a JPG, JPEG, PNG or WebP file up to 15 MB.

  2. Queue

    A private owner-scoped job is created and claimed by the image worker.

  3. Analyze

    The worker normalizes the image, runs the configured scan profile and records typed scanner results.

  4. Aggregate

    Completed evidence is combined into one result while optional scanner failures remain isolated.

  5. Return

    The web app polls the job and renders the report when processing is complete.

Image signal families

Image checks in the IA Checker pipeline
FamilyExamplesPurpose
Source signatureMetadata, EXIF, C2PARead available creation and editing context
Visible labelsTesseract OCRFind explicit AI labels and provider marks
Pixel forensicsFFT, DCT, residual noise, blur, edgesMeasure file-level patterns
Specialist modelsSSP and CO-SPYCompare texture, semantic and pixel representations
Primary visual modelDeployment-configured visual bundleAdd a global scene-level reading

File handling and retention

The source image is held for the short processing window, with a default retention of about one hour, then removed. The derived typed result can remain for reliability and report access, while the original image is not copied into text history.

Owner scoping applies to job creation, status and results. Browser code cannot request another account's job or select a deeper profile than the server permits.