accountable-record-py

v0.4.2 suspicious
5.0
Medium Risk

(No description)

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows minimal risk in terms of network usage, shell execution, obfuscation, and credential harvesting. However, the metadata risk score is moderately high due to sparse author details and potential inactivity, which raises concerns about its provenance.

  • Sparse author details
  • Potential inactivity of the maintainer
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external API access.
  • Shell: No shell execution patterns detected, indicating no direct system command execution by the package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author's details are sparse, and the maintainer seems new or inactive, raising some suspicion.

🔬 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: structural-explainability.org>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ 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 accountable-record-py 
Create a mini-application called 'Accountable Expense Tracker' using Python and the 'accountable-record-py' package. This application will allow users to log their daily expenses, track them over time, and generate reports based on various criteria such as category, date range, and total amount spent. The application should have the following core functionalities:

1. User Authentication: Allow users to create accounts and log in securely.
2. Expense Logging: Users should be able to add new expenses with details like date, amount, category, and description.
3. Expense Tracking: Display a summary of all logged expenses, including total amounts spent per category and overall.
4. Reporting: Generate detailed reports based on user-defined criteria such as specific date ranges or categories.
5. Data Visualization: Utilize the 'accountable-record-py' package to ensure that all data operations are transparent and verifiable, providing accountability in financial tracking.
6. Backup and Restore: Implement functionality to back up and restore user data to prevent loss.
7. User Interface: Design a simple yet intuitive command-line interface for ease of use.

The 'accountable-record-py' package will be crucial in ensuring that every data operation within the application is logged and can be audited for transparency and accountability. This means that when users log expenses, the application should record not only the expense itself but also who made the entry, when it was made, and any changes made thereafter. Additionally, the package should support the creation of audit trails for each transaction, allowing for easy verification of the integrity of the recorded data.