gchq/CyberChef · error · OperationError

Unsupported file type (supported: jpg,png,pbm,bmp) or no…

Error message

Unsupported file type (supported: jpg,png,pbm,bmp) or no file provided

What it means

Thrown by OpticalCharacterRecognition.run when isImage(input) returns false — the input is not a recognised image (jpg, png, pbm, bmp). Tesseract can only process raster images, so non-image data or unsupported formats (e.g. tiff, webp) are rejected before the worker is created.

Solutions

1. Convert the source to PNG, JPG, PBM, or BMP before feeding it in.
2. For PDFs, rasterise to PNG first (e.g. via a render operation or external tool).
3. Ensure the upstream op outputs an ArrayBuffer containing the raw image bytes.
4. Verify the buffer is non-empty and begins with the correct magic bytes.

import { isImage } from "core/lib/FileType.mjs";
if (!isImage(input)) {
  // convert to PNG/JPG/PBM/BMP before running OCR
}

const isOCRImage = (buf) => Boolean(isImage(buf));

try { await chef.bake("Optical Character Recognition", args, input); }
catch (e) { if (e.message.startsWith("Unsupported file type")) convertToPNG(); else throw e; }

When it happens

Trigger: run(input, args) with an ArrayBuffer whose magic bytes are not a supported image type. Feeding a PDF, TIFF, WebP, text, or empty buffer, or a file with a spoofed extension, trips this.

Common situations: Dropped a PDF or TIFF (Tesseract supports them but CyberChef's sniffer gate does not); uploaded a screenshot saved as WebP; upstream operation produced a non-ArrayBuffer; empty buffer from a failed load; file renamed to .png but actually a document.

Related errors

• Invalid file type.
• Invalid file type.
• Invalid file type.
• Invalid file type.
• Invalid file type.

AI-assisted analysis of gchq/CyberChef@4290ea7539 (2026-08-13). Data as JSON: /api/errors/e8f973a36c7794b7. Report an issue: GitHub.

Appendix: source

Thrown at src/core/operations/OpticalCharacterRecognition.mjs:63

                value: OEM_MODES,
                defaultIndex: 1
            }
        ];
    }

    /**
     * @param {ArrayBuffer} input
     * @param {Object[]} args
     * @returns {string}
     */
    async run(input, args) {
        const [showConfidence, oemChoice] = args;

        if (!isWorkerEnvironment()) throw new OperationError("This operation only works in a browser");

        const type = isImage(input);
        if (!type) {
            throw new OperationError("Unsupported file type (supported: jpg,png,pbm,bmp) or no file provided");
        }

        const assetDir = `${self.docURL}/assets/`;
        const oem = OEM_MODES.indexOf(oemChoice);

        try {
            self.sendStatusMessage("Spinning up Tesseract worker...");
            const image = `data:${type};base64,${toBase64(input)}`;
            const worker = await createWorker("eng", oem, {
                workerPath: `${assetDir}tesseract/worker.min.js`,
                langPath: `${assetDir}tesseract/lang-data`,
                corePath: `${assetDir}tesseract/tesseract-core.wasm.js`,
                logger: progress => {
                    if (isWorkerEnvironment()) {
                        self.sendStatusMessage(`Status: ${progress.status}${progress.status === "recognizing text" ? ` - ${(parseFloat(progress.progress)*100).toFixed(2)}%`: "" }`);
                    }
                }
            });

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