Comprehensive Automated Doc Verification

# CertiSecure - Secure Marksheet Generator & Validator CertiSecure is a web application designed to generate tamper-proof marksheet PDFs and validate them using cryptographic hashing and strict content verification. ## Features ### 1. Secure Generation - **Data Hashing**: Creates a SHA-256 hash of the student's text details (Name, Marks, etc.). - **Image Hashing**: Normalizes the profile photo to JPEG and calculates its SHA-256 hash to prevent format-based verification errors. - **QR Code Embedding**: Embeds a QR code containing the digital signature (hashes) of both the text and the image. - **Visual Security**: Adds a visual border to the profile photo and embeds the specific JPEG stream that was hashed. ### 2. Strict Validation - **Content Extraction**: Extracts raw text and images from the uploaded PDF. - **Integrity Check**: Re-calculates hashes of the extracted content and compares them byte-for-byte with the data stored in the QR code. - **Visual Tamper Detection**: Automatically fails validation if any PDF annotations or overlays (common in "fill and sign" editors) are detected. - **Feedback**: Provides detailed pass/fail reports for text, photo, and visual layer integrity. ## Prerequisites - Python 3.8+ - Pip (Python Package Manager) ## Installation Guide 1. **Clone/Download** this project folder. 2. **Open a terminal** inside the project folder. 3. **Install Dependencies**: ```bash pip install -r requirements.txt ``` ## Step-by-Step Usage ### Starting the Server Run the application using Python: ```bash python app.py ``` The server will start at `http://127.0.0.1:5000`. ### Generating a Marksheet 1. Open your browser and go to `http://127.0.0.1:5000`. 2. Fill in the form (Name, Father's Name, Institution, Roll No, Marks). 3. Upload a Profile Photo (JPG/PNG). 4. Click **Generate Secured PDF**. 5. The secured PDF will run and download automatically. ### Validating a Marksheet 1. Go to the **Validate Document** section on the home page. 2. Upload a Marksheet PDF (either the original or a generic file). 3. Click **Run Verification**. 4. **Check the Results**: - **Authentic**: All hashes match, and no tampering detected. - **Invalid / Tampered**: The text or photo has been changed, or someone added visual annotations. ## Technical Notes - **Image Handling**: To ensure consistency, all uploaded photos are converted to JPEG quality 95 before hashing. This ensures the hash stored in the QR always matches the image embedded in the PDF. - **Libraries Used**: - `Flask` (Web Framework) - `ReportLab` (PDF Generation) - `PyMuPDF (fitz)` (PDF Reading/Extraction) - `OpenCV` (QR Code Detection) - `Pillow` (Image Processing) Automated Document Verification System for Official Documentation - https://1drv.ms/w/c/87C32D068B13D74E/IQC60j2_IM9eRa21Bq-kq1lLAemn0T-eCkr7fRg1lZ1jG6E?e=SjqEtO