aurabrain

v0.5.1 suspicious
4.0
Medium Risk

AuraBrain — Universal cognitive architecture SDK with anticipatory priming, causal inference, and adaptive forgetting

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a moderate risk score due to potential network and metadata risks, but lacks clear indicators of malicious intent.

  • moderate network risk
  • suspicious metadata
Per-check LLM notes
  • Network: The observed network call pattern suggests the package is likely making HTTP requests to a base URL, which could be for legitimate purposes like API interactions.
  • Shell: No shell execution patterns were detected, indicating no immediate risk of command execution from this package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, suggesting no immediate threat to secrets or credentials.
  • Metadata: Suspicious non-HTTPS link and new maintainer account raise some concerns.

📦 Package Quality Overall: Medium (5.8/10)

✦ High Test Suite 9.0

Test suite present — 1 test file(s) found

  • Test runner config found: pyproject.toml
  • 1 test file(s) detected (e.g. test_sdk.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://aurabrain.io/docs
  • Detailed PyPI description (1012 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
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 61 commits in PixelAIWizard22/aurabrain.io
  • Two distinct contributors found

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • p("/") self._client = httpx.Client(base_url=self.base_url, timeout=timeout) # ── Health &
✓ 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 score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://127.0.0.1:3000
✓ Git Repository History

Repository PixelAIWizard22/aurabrain.io appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "AuraBrain" 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 aurabrain 
Create a personal cognitive assistant application using the 'aurabrain' package that helps users manage their daily tasks and anticipate upcoming events based on their behavior patterns. The application should integrate the following key functionalities:

1. **Task Management**: Users can input daily tasks and set reminders. The application should use the anticipatory priming feature of 'aurabrain' to suggest tasks based on the user's past behavior.
2. **Event Anticipation**: Based on historical data, the application predicts important events (like meetings, deadlines) that the user might forget about and reminds them in advance.
3. **Adaptive Forgetting**: Over time, the application should adapt its suggestions and reminders according to the user's engagement and relevance of the tasks, utilizing the adaptive forgetting mechanism provided by 'aurabrain'.
4. **Causal Inference**: When a task is completed or a reminder is triggered, the application should analyze why certain tasks were forgotten or why specific reminders were effective, enhancing future predictions and recommendations.
5. **User Interface**: Develop a simple and intuitive UI where users can easily interact with the app, view their task list, upcoming events, and feedback from the application's cognitive analysis.

The goal is to create an intelligent tool that not only helps users stay organized but also learns from their interactions to improve over time. Use the 'aurabrain' package's documentation and examples as a starting point for integrating these advanced cognitive features into your application.

💬 Discussion Feed

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