aa-ledger

v3.0.1 suspicious
4.0
Medium Risk

Character and Corporation statistics, including detailed information on ESS, Ratting, Trading, Mining, and other activities.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low individual risks across all categories except metadata, where the maintainer's account status raises some concern. This combination suggests potential caution but does not confirm malicious activity.

  • Low network, shell, obfuscation, and credential risks.
  • Suspicion due to new or inactive maintainer account with incomplete information.
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell executions detected, indicating no immediate risk of 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 and lacks a full author name, which raises some suspicion but does not strongly indicate malicious intent.

🔬 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: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository Geuthur/aa-ledger 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 aa-ledger 
Create a comprehensive financial analysis tool for EVE Online players using the 'aa-ledger' Python package. This tool will allow users to input their game activity data (such as mining, trading, ratting, etc.) and generate detailed reports and visualizations. The application should have the following features:

1. **User Input**: Allow users to input their character and corporation activity data manually or import it from CSV files.
2. **Data Processing**: Utilize 'aa-ledger' to process the input data, generating detailed statistics for each type of activity (ESS, Ratting, Trading, Mining).
3. **Report Generation**: Automatically generate comprehensive reports based on the processed data, including total earnings, losses, profit margins, and activity trends over time.
4. **Visualization**: Implement graphs and charts using libraries like Matplotlib or Plotly to visualize the financial performance of the user's activities.
5. **Corporation Overview**: Provide an overview of the corporation's financial health, showing aggregated data across all members.
6. **Activity Comparison**: Enable comparison between different types of activities to help users identify the most profitable strategies.
7. **User Interface**: Develop a simple and intuitive web interface using Flask or Django to make the tool accessible and user-friendly.

The 'aa-ledger' package should be utilized extensively for its ability to handle complex EVE Online financial data, providing accurate and detailed analytics. Your task is to design and implement this tool from scratch, ensuring it is both functional and easy to use.