AI-Powered PDF Security Auditor

AI-Powered PDF Security Auditor analyzes uploaded PDF documents to identify potential risks, sensitive information leaks, and malware threats.

It uses an advanced LLM (Groq-powered) to summarize content, assess data exposure, and classify security risks.

The tool produces a professional PDF report highlighting document metadata, AI-driven risk level, detected sensitive data, and malware analysis results(with providing Report link for users)

What Happens When You Upload a PDF

Each time you upload a PDF, the system performs a full end-to-end security analysis and generates a professional AI-based report.

Here’s what’s inside:

1️⃣ Executive Summary (AI-Generated)

The AI-Powered PDF Security Auditor intelligently analyzes uploaded PDF files using Groq’s advanced LLM engine.

It automatically reads the document, cleans and interprets its text, and then generates a concise 5-sentence summary that captures the most important insights.

The AI highlights the main topic and purpose, detects sensitive or security-related content , and identifies the document’s structure and potential risk areas.

This summary gives users a fast, high-level understanding of what the PDF contains before running deeper scans like regex-based sensitive data detection or malware analysis.

2️⃣ Document Metadata

Extracted automatically from the PDF header:

Author

Title

Creation Date

Producer

Number of Pages

File Size

Purpose: Helps identify the document’s origin, authenticity, and technical details.

3️⃣ Sensitive Information & Exposure Analysis

This section combines LLM reasoning and regex pattern scanning.

The Sensitive Data Scanner automatically analyzes each page of the uploaded PDF using predefined regex patterns to detect confidential or personally identifiable information.

It searches for emails, passwords, tokens, API keys, phone numbers, credit card numbers, IPs, and other sensitive data across the document.

For each finding, it records the page number, data type, exact term, and surrounding text context to show where and how the data appears.

All detected entries are then exported into a CSV report for further review.

AI Risk Assessment

The LLM classifies the document’s exposure risk into:

Low — minimal exposure

Medium — some sensitive data present

High — serious data exposure risk

It also provides a detailed explanation outlining the reasoning behind the assigned risk level.

4️⃣ Malware Scan Summary (VirusTotal Integration)

This stage computes the file’s SHA-256 fingerprint to uniquely identify the document and verify integrity. It checks whether that fingerprint has a prior scan result, and if needed submits the file for live analysis. The tool then aggregates detection statistics and produces direct link to the full VirusTotal report so reviewers can inspect engine-by-engine detections, timestamps, and other forensic details.