astrocyte

v0.15.0 suspicious
4.0
Medium Risk

Open-source memory framework for AI agents

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some signs of potential misuse due to its ability to handle /etc/passwd content, despite having low risks in network, shell, and obfuscation categories. The incomplete metadata adds to the suspicion.

  • Credential risk due to handling /etc/passwd
  • Incomplete author information and single-package maintainer
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require internet access.
  • Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
  • Obfuscation: No obfuscation patterns detected in the provided information.
  • Credentials: The capability to pass and return /etc/passwd file content could indicate potential misuse for credential harvesting.
  • Metadata: The author information is incomplete and the maintainer has only one package, which could indicate a less experienced or potentially suspicious user.

📦 Package Quality Overall: Medium (5.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://astrocyteai.github.io/astrocyte/
  • Detailed PyPI description (7887 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 409 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in AstrocyteAI/astrocyte
  • Two distinct contributors found

🔬 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 score 2.5

Found 1 credential access pattern(s)

  • contain — a caller can # pass /etc/passwd and resolve() returns it unchanged. ``_safe_resolve`` # va
✓ 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 AstrocyteAI/astrocyte 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 astrocyte 
Create a personalized learning assistant application using the Python package 'astrocyte', which serves as an open-source memory framework for AI agents. This application will help users track their learning progress, manage study materials, and provide personalized recommendations based on their interactions. Here's a detailed plan on how to proceed:

1. **Setup**: Begin by installing the necessary packages, including 'astrocyte'. Ensure you have a Python environment set up.
2. **User Interface**: Develop a simple user interface where users can log in or sign up. This could be a command-line interface (CLI) or a basic web interface using Flask.
3. **Memory Management**: Utilize 'astrocyte' to create a robust memory management system for storing and retrieving user data such as study habits, topics covered, and performance metrics. Use 'astrocyte' features like persistent storage and retrieval of user data.
4. **Learning Tracker**: Implement a feature where users can input their study sessions, including topics studied and duration. Use 'astrocyte' to store these sessions and analyze patterns over time to suggest optimal study times and topics.
5. **Study Material Management**: Allow users to upload and categorize study materials (e.g., PDFs, notes). 'Astrocyte' can be used here to tag and organize these resources, making them easily searchable.
6. **Personalized Recommendations**: Based on user interaction and study patterns, provide personalized recommendations for study topics and materials. Use 'astrocyte' to analyze past behaviors and preferences.
7. **Feedback Loop**: Incorporate a feedback mechanism where users can rate the effectiveness of the recommended study materials and topics. Use this feedback to improve future recommendations.
8. **Integration with External APIs**: Consider integrating with external APIs for additional resources or services (e.g., educational content from Coursera).
9. **Testing and Deployment**: Thoroughly test your application to ensure all features work as expected. Deploy your application to a platform like Heroku or AWS if it's a web app.

This project will not only demonstrate the power of 'astrocyte' but also provide a practical tool for learners looking to optimize their study routines.

💬 Discussion Feed

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