CamScanner Image Detect Tampering

Overview

CamScanner provides a manipulation-detection engine that determines whether an image has been PS-edited, spliced, retouched, or otherwise tampered with. The workflow is a 2-step pipeline: upload the image, then validate it with validate_mode: 1. Unlike conversion skills, this skill does not produce a file — the validate step returns a JSON result whose key fields (is_tampered, result_text) should be reported back to the user directly.

When to Use

• User asks whether an image has been photoshopped, retouched, or manipulated
• User wants to verify the authenticity of a photo or scanned document
• User asks "is this PS-ed / tampered / edited?" or similar authenticity questions
• User shares an image and explicitly asks whether it has been modified

Presenting the Result

• Always read is_tampered and result_text from the response and report them in plain language.
• Match the user's language. result_text is returned in Chinese by the API. If the user asked in English (or any other language), translate/rephrase it into that language. If the user asked in Chinese, you can use result_text as-is.
• Do not claim tampering when is_tampered is false; do not claim an image is clean when is_tampered is true.

Privacy & Data

> Important: Privacy & Data Flow Notice

>

> - Third-party service: This skill sends your files to CamScanner's official servers (ai-tools.camscanner.com) for processing.

> - Data retention: CamScanner servers process your files in real-time. Files are not permanently stored on the server.

> - Result: Only a JSON detection result is returned — no file is downloaded.

API Reference

Base URL: https://ai-tools.camscanner.com

Supported Validations

Step 1: Upload Image

BASE="https://ai-tools.camscanner.com"

IN_FILE_ID=$(curl -sS -X POST "$BASE/v1/tools/upload_file/execute" \
  -H "Content-Type: application/octet-stream" \
  --data-binary "@/path/to/image.jpg" | jq -r '.tool_result.data.file_id')

Response:

{
  "code": 200,
  "tool": "upload_file",
  "tool_result": {
    "success": true,
    "data": {
      "file_id": "file_1741857600_ab12cd34ef56.jpg",
      "size": 24576
    }
  }
}

Step 2: Validate Image (Detect Tampering)

curl -sS -X POST "$BASE/v1/tools/validate_image/execute" \
  -H "Content-Type: application/json" \
  -d "{\"file_id\":\"$IN_FILE_ID\",\"validate_mode\":1}"

Response (tampered example):

{
  "code": 200,
  "tool": "validate_image",
  "tool_result": {
    "success": true,
    "data": {
      "engine": "manipulationdetection",
      "file_id": "file_xxx.jpg",
      "is_tampered": true,
      "result_text": "检测到图片存在 PS/篡改痕迹",
      "review_state": "auto_checked",
      "validate_mode": 1
    },
    "metadata": {
      "engine": "manipulationdetection",
      "is_tampered": true,
      "result_text": "检测到图片存在 PS/篡改痕迹",
      "review_state": "auto_checked",
      "validate_mode": 1
    }
  }
}

Interpreting the Result

Quick Reference: Complete Pipeline

Detect whether an image has been PS-edited (two-step, reads JSON result):

BASE="https://ai-tools.camscanner.com"
INPUT_IMAGE="/path/to/image.jpg"

# Upload
IN_FILE_ID=$(curl -sS -X POST "$BASE/v1/tools/upload_file/execute" \
  -H "Content-Type: application/octet-stream" \
  --data-binary "@$INPUT_IMAGE" | jq -r '.tool_result.data.file_id')

# Validate and extract key fields
RESULT=$(curl -sS -X POST "$BASE/v1/tools/validate_image/execute" \
  -H "Content-Type: application/json" \
  -d "{\"file_id\":\"$IN_FILE_ID\",\"validate_mode\":1}")

IS_TAMPERED=$(echo "$RESULT" | jq -r '.tool_result.data.is_tampered')
RESULT_TEXT=$(echo "$RESULT" | jq -r '.tool_result.data.result_text')

echo "is_tampered: $IS_TAMPERED"
echo "result_text: $RESULT_TEXT"

Common Mistakes

Error Handling

Check each step before proceeding:

# After upload
if [ -z "$IN_FILE_ID" ] || [ "$IN_FILE_ID" = "null" ]; then
  echo "Upload failed"; exit 1
fi

# After validate
if [ "$IS_TAMPERED" = "null" ] || [ -z "$IS_TAMPERED" ]; then
  echo "Validation failed"; exit 1
fi