backinmyday

v0.1.0 suspicious
4.0
Medium Risk

CLI archaeology tool for the AI era — discover what the LLM landscape looked like when your code was written.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has minimal risk indicators such as no network calls, shell executions, or credential harvesting. However, its metadata and lack of maintainership history raise concerns.

  • Limited maintainer history
  • No associated GitHub repository
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communication.
  • Shell: No shell execution patterns detected, indicating the package does not execute commands that could be used for malicious purposes.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package is new with limited maintainer history and no associated GitHub repository, which raises some suspicion but not enough to conclusively determine malintent.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 4 test file(s) found

  • Test runner config found: pyproject.toml
  • 4 test file(s) detected (e.g. test_cli.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (4069 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 17 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 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

No author email provided

✓ 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

  • Only one version has ever been released — brand new package
  • Author "Fran-cois" 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 backinmyday 
Create a time-traveling developer's companion called 'CodeTimeCapsule'. This application will allow developers to input any piece of their old code and receive insights on how the current language models (LLMs) would have perceived and interacted with that code at the time it was written. The goal is to provide context and perspective on the evolution of AI and coding practices.

Steps to create this mini-app:
1. Setup the environment with Python and install the 'backinmyday' package.
2. Design a simple GUI or CLI interface where users can paste their old code snippets.
3. Implement a feature that allows users to select a specific date or version of their code repository.
4. Use the 'backinmyday' package to simulate an AI response from that point in time, providing comments, suggestions, and comparisons with modern AI capabilities.
5. Integrate a feature that highlights differences between the AI feedback from the past and present, offering a comparative analysis.
6. Add functionality to save these analyses for future reference or comparison.
7. Optionally, include a feature that visualizes the timeline of changes in AI perception over different versions of the same codebase.

Suggested Features:
- Code snippet history tracking.
- Interactive timeline visualization.
- Export analysis reports.
- Integration with popular version control systems for automatic code fetching.

How 'backinmyday' is utilized:
- The core function of 'backinmyday' will be used to generate historical AI responses based on the provided code snippet and the specified date/version. This involves understanding the LLM landscape at that time and simulating how an AI model from that period would interact with the given code.
- Utilize 'backinmyday' to analyze trends and shifts in AI understanding of coding practices over time, which can then be presented through the comparative analysis feature.

💬 Discussion Feed

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