camscanner-image-detect-tampering

name	camscanner-image-detect-tampering
description	Use CamScanner to detect whether an image has been PS-edited, manipulated, or tampered with. Powered by a manipulation-detection engine that identifies photo-editing traces, splicing, retouching, and other signs of tampering. Returns a JSON result with `is_tampered` (boolean) and `result_text` (human-readable). Use when the user asks whether a photo is genuine, wants to verify an image's authenticity, or asks "is this PS-ed / photoshopped / edited". Triggers on "检测图片是否PS", "是否被篡改", "图片验真", "PS检测", "detect image tampering", "is this photoshopped", "check if image was edited", or when the user shares an image and asks whether it has been modified.
metadata	{"author":"CamScanner","version":"1.0","openclaw":{"emoji":"🔍","requires":{"bins":["curl","jq"]}},"homepage":"https://www.camscanner.com"}

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

source_type	validate_mode	Detection	Engine
image	1	PS / tampering detection	manipulationdetection

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,
       
       
       
    
  

Interpreting the Result

Field	Type	Meaning
is_tampered	boolean	true = tampering detected, false = no tampering detected
result_text	string	Human-readable conclusion (Chinese by default — translate for other languages)
review_state	string	Review status (e.g. auto_checked) — informational, not user-facing
validate_mode	integer	Echo of the requested mode (always 1 for PS/tampering detection)

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

Mistake	Fix
Wrong Content-Type on upload	Upload uses application/octet-stream, not multipart/form-data
Using GET instead of POST	Both endpoints use POST
Passing validate_mode as a string	validate_mode is an integer — use 1, not "1"
Including output_mode in the request	validate_image does not use output_mode; it always returns JSON
Treating a missing is_tampered as safe	Always check code == 200 and tool_result.success == true before reading
Reporting result_text verbatim in EN	result_text is Chinese; translate to match the user's language

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