FileAnalyzer

FileAnalyzer is an ultra-complete sensitive file analysis tool for bug bounty hunters and security researchers. It allows downloading documents like PDF, DOCX, DOCM, XLSX, XLSM, PPTX, or PPTM from public or private URLs, extracting content, and detecting sensitive information using keywords, regex patterns, metadata analysis, macros, and fuzzy search.

FileAnalyzer is optimized to detect real sensitive information, including corporate emails, IBANs, AWS keys, JWTs, OAuth tokens, API keys, internal endpoints, local paths, and much more.

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🚀 Features

• Supports multiple file formats:
  • PDF → pdfplumber
  • DOCX/DOCM → python-docx
  • XLSX/XLSM → openpyxl
  • PPTX/PPTM → python-pptx
• Detects sensitive information using:
  • Predefined regex (emails, IBAN, JWT, AWS/GCP/Azure keys, API tokens, credit cards, IPs, internal URLs).
  • User-defined keywords (e.g., confidential, internal, secret).
  • Fuzzy keyword matching.
  • Metadata extraction (author, software, creation/modification date).
  • Comments and hidden content.
  • Macros/scripts detection in Office files.
  • Local file paths in documents
• Risk scoring and classification (LOW, MEDIUM, HIGH)
• Automatic PoC generation for findings.
• JSON export of results.
• Risk filtering (--silent) to show only HIGH.
• Download timeout and max file size control.
• Easy integration into bug bounty pipelines.

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🧠 What it detects

FileAnalyzer focuses on confidential and corporate data, including:

• Corporate and generic emails (*@company.com, *@example.com)
• IBAN, SWIFT/BIC, and credit card numbers
• AWS, GCP, Azure, Slack, Discord, GitHub, and generic API keys
• JWT and OAuth tokens
• User-defined keywords (confidential, internal, do not distribute, etc.)
• Metadata in documents (author, software, date, comments)
• Macros or scripts in Office documents
• Internal URLs, API endpoints, and private/public IPs
• Local file paths (Windows & Linux)
• Fuzzy matches for approximate keywords

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📦 Installation

git clone http://github.com/yourusername/FileAnalyzer.git
cd FileAnalyzer
pip install -r requirements.txt

🔍 Example output

⚙️ Usage

Prepare files

1. Create a file urls.txt containing all the URLs of the documents to analyze (one per line):

https://example.com/confidential.docx
https://example.com/report.pdf

2. Create a file keywords.txt with keywords to search:

confidential
internal use only
secret
password
token

Scan a single URL

python3 main.py -u https://example.com/financial_report.xlsx keywords.txt --poc --json

Basic scan

python3 main.py urls.txt keywords.txt

Show only high-risk findings

python3 main.py urls.txt keywords.txt --silent

Generate PoC and JSON results

python3 main.py urls.txt keywords.txt --poc --json

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🔍 Example output

[HIGH] https://example.com/sample_confidential.docx (score: 90)
  └─ Corporate email: john.doe@company.com
  └─ Keyword found: confidential
  └─ Fuzzy keyword match: confidential (92%)
  └─ Password placeholder: password="12345"
  └─ Author: Internal User
  └─ Macros detected!

[MEDIUM] https://example.com/financial_report.xlsx (score: 45)
  └─ IBAN: DE89370400440532013000
  └─ Credit card: 4111 1111 1111 1111
  └─ Internal URL: http://dev.company.local/api/v1/getData

PoC file generated in poc/https___example_com_confidential_docx.txt.

JSON file generated if --json is used.

📜 License

MIT License

🛡️ Responsible Usage

This tool is intended for:

• Authorized security testing.
• Bug bounty programs within scope.
• Research environments.

Important: Do not publish or register potentially private packages without authorization. Always follow responsible disclosure policies.