PDFSentinel

v3.0.1 safe
3.0
Low Risk

PDF Sentinel is a lightweight safety inspection library for PDF documents. It detects oversized, vector-heavy, or otherwise resource-intensive pages (like blueprints) that could slow down or crash OCR and pipelines.

🤖 AI Analysis

Final verdict: SAFE

The package PDFSentinel appears to be safe based on the analysis. It does not exhibit any signs of malicious activity, such as network calls, shell execution, or obfuscation.

  • No network calls detected.
  • No shell execution detected.
  • No obfuscation patterns detected.
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell execution detected, indicating no direct system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets and credentials.
  • Metadata: The maintainer has a new or inactive account with incomplete author information.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: not-empty.org>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository not-empty/pdf-sentinel-python appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with PDFSentinel 
Create a desktop application called 'SafeScan' using Python that helps users identify potentially problematic PDF files before processing them through OCR systems. SafeScan should integrate the PDFSentinel library to analyze PDF documents and flag any oversized or vector-heavy pages that could cause issues during OCR processing.

Step 1: Design the User Interface
- Develop a simple yet user-friendly GUI using Tkinter or PyQt.
- Include a file explorer button to allow users to select one or multiple PDF files.
- Display a list of selected files and their status (e.g., clean, flagged).

Step 2: Implement File Analysis
- Utilize the PDFSentinel package to scan each selected PDF document.
- Identify pages that exceed a certain size threshold or contain excessive vector graphics.
- Provide a summary of the analysis including total number of pages, flagged pages, and overall document size.

Step 3: Add Additional Features
- Include a feature to export a report detailing the analysis results in CSV format.
- Allow users to specify custom thresholds for page size and vector content.
- Implement a preview mode where users can view flagged pages before exporting.

Step 4: Enhance Usability
- Ensure the application provides real-time feedback as it processes files.
- Offer tooltips or a help section explaining what constitutes a 'problematic' PDF.
- Include error handling to gracefully manage unsupported file types or corrupted documents.